mcp/zen

Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini C...

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镜像标签列表与下载命令

Zen MCP Server

Bridges multiple AI models and CLIs, enabling orchestrated workflows across Claude Code, Gemini CLI, Codex CLI, and other AI development tools.

https://www.anthropic.com/news/model-context-protocol

MCP Info

Attribute	Details
Docker Image	https://hub.docker.com/repository/docker/mcp/zen
Author	https://github.com/BeehiveInnovations
Repository	https://github.com/beehiveinnovations/zen-mcp-server

Image Building Info

Attribute	Details
Dockerfile	https://github.com/beehiveinnovations/zen-mcp-server/blob/7afc7c1cc96e23992c8f105f960132c657883bb1/Dockerfile
Commit	`7afc7c1cc96e23992c8f105f960132c657883bb1`
Docker Image built by	Docker Inc.
Docker Scout Health Score
Verify Signature	`COSIGN_REPOSITORY=mcp/signatures cosign verify mcp/zen --key https://raw.githubusercontent.com/docker/keyring/refs/heads/main/public/mcp/latest.pub`
Licence	Other

Available Tools (18)

Tools provided by this Server	Short Description
`analyze`	Performs comprehensive code analysis with systematic investigation and expert validation.
`apilookup`	Use this tool automatically when you need current API/SDK documentation, latest version info, breaking changes, deprecations, migration guides, or official release notes.
`challenge`	Prevents reflexive agreement by forcing critical thinking and reasoned analysis when a statement is challenged.
`chat`	General chat and collaborative thinking partner for brainstorming, development discussion, getting second opinions, and exploring ideas.
`clink`	Link a request to an external AI CLI (Gemini CLI, Qwen CLI, etc.) through PAL MCP to reuse their capabilities inside existing workflows.
`codereview`	Performs systematic, step-by-step code review with expert validation.
`consensus`	Builds multi-model consensus through systematic analysis and structured debate.
`debug`	Performs systematic debugging and root cause analysis for any type of issue.
`docgen`	Generates comprehensive code documentation with systematic analysis of functions, classes, and complexity.
`listmodels`	Shows which AI model providers are configured, available model names, their aliases and capabilities.
`planner`	Breaks down complex tasks through interactive, sequential planning with revision and branching capabilities.
`precommit`	Validates git changes and repository state before committing with systematic analysis.
`refactor`	Analyzes code for refactoring opportunities with systematic investigation.
`secaudit`	Performs comprehensive security audit with systematic vulnerability assessment.
`testgen`	Creates comprehensive test suites with edge case coverage for specific functions, classes, or modules.
`thinkdeep`	Performs multi-stage investigation and reasoning for complex problem analysis.
`tracer`	Performs systematic code tracing with modes for execution flow or dependency mapping.
`version`	Get server version, configuration details, and list of available tools.

Tools Details

Tool: analyze

Performs comprehensive code analysis with systematic investigation and expert validation. Use for architecture, performance, maintainability, and pattern analysis. Guides through structured code review and strategic planning.

Parameters	Type	Description
`findings`	`string`	Summary of discoveries from this step, including architectural patterns, tech stack assessment, scalability characteristics, performance implications, maintainability factors, and strategic improvement opportunities. IMPORTANT: Document both strengths (good patterns, solid architecture) and concerns (tech debt, overengineering, unnecessary complexity). In later steps, confirm or update past findings with additional evidence.
`model`	`string`	Currently in auto model selection mode. CRITICAL: When the user names a model, you MUST use that exact name unless the server rejects it. If no model is provided, you may use the `listmodels` tool to review options and select an appropriate match. Top models: gpt-5.2 (score 100, 400K ctx, thinking, code-gen); gpt-5.1-codex (score 100, 400K ctx, thinking, code-gen); gemini-2.5-pro (score 100, 1.0M ctx, thinking, code-gen); gemini-3-pro-preview (score 100, 1.0M ctx, thinking, code-gen); gpt-5.2-pro (score 100, 400K ctx, thinking, code-gen); +26 more via `listmodels`.
`next_step_required`	`boolean`	Set to true if you plan to continue the investigation with another step. False means you believe the analysis is complete and ready for expert validation.
`step`	`string`	The analysis plan. Step 1: State your strategy, including how you will map the codebase structure, understand business logic, and assess code quality, performance implications, and architectural patterns. Later steps: Report findings and adapt the approach as new insights emerge.
`step_number`	`integer`	The index of the current step in the analysis sequence, beginning at 1. Each step should build upon or revise the previous one.
`total_steps`	`integer`	Your current estimate for how many steps will be needed to complete the analysis. Adjust as new findings emerge.
`analysis_type`	`string` optional	Type of analysis to perform (architecture, performance, security, quality, general)
`confidence`	`string` optional	Your confidence in the analysis: exploring, low, medium, high, very_high, almost_certain, or certain. 'certain' indicates the analysis is complete and ready for validation.
`continuation_id`	`string` optional	Unique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.
`files_checked`	`array` optional	List all files examined (absolute paths). Include even ruled-out files to track exploration path.
`images`	`array` optional	Optional absolute paths to architecture diagrams or visual references that help with analysis context.
`issues_found`	`array` optional	Issues or concerns identified during analysis, each with severity level (critical, high, medium, low)
`output_format`	`string` optional	How to format the output (summary, detailed, actionable)
`relevant_context`	`array` optional	Methods/functions identified as involved in the issue
`relevant_files`	`array` optional	Subset of files_checked directly relevant to analysis findings (absolute paths). Include files with significant patterns, architectural decisions, or strategic improvement opportunities.
`temperature`	`number` optional	0 = deterministic · 1 = creative.
`thinking_mode`	`string` optional	Reasoning depth: minimal, low, medium, high, or max.
`use_assistant_model`	`boolean` optional	Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

This tool is read-only. It does not modify its environment.

Tool: apilookup

Use this tool automatically when you need current API/SDK documentation, latest version info, breaking changes, deprecations, migration guides, or official release notes. This tool searches authoritative sources (official docs, GitHub, package registries) to ensure up-to-date accuracy.

Parameters	Type	Description
`prompt`	`string`	The API, SDK, library, framework, or technology you need current documentation, version info, breaking changes, or migration guidance for.

This tool is read-only. It does not modify its environment.

Tool: challenge

Prevents reflexive agreement by forcing critical thinking and reasoned analysis when a statement is challenged. Trigger automatically when a user critically questions, disagrees or appears to push back on earlier answers, and use it manually to sanity-check contentious claims.

Parameters	Type	Description
`prompt`	`string`	Statement to scrutinize. If you invoke `challenge` manually, strip the word 'challenge' and pass just the statement. Automatic invocations send the full user message as-is; do not modify it.

This tool is read-only. It does not modify its environment.

Tool: chat

General chat and collaborative thinking partner for brainstorming, development discussion, getting second opinions, and exploring ideas. Use for ideas, validations, questions, and thoughtful explanations.

Parameters	Type	Description
`model`	`string`	Currently in auto model selection mode. CRITICAL: When the user names a model, you MUST use that exact name unless the server rejects it. If no model is provided, you may use the `listmodels` tool to review options and select an appropriate match. Top models: gpt-5.2 (score 100, 400K ctx, thinking, code-gen); gpt-5.1-codex (score 100, 400K ctx, thinking, code-gen); gemini-2.5-pro (score 100, 1.0M ctx, thinking, code-gen); gemini-3-pro-preview (score 100, 1.0M ctx, thinking, code-gen); gpt-5.2-pro (score 100, 400K ctx, thinking, code-gen); +26 more via `listmodels`.
`prompt`	`string`	Your question or idea for collaborative thinking to be sent to the external model. Provide detailed context, including your goal, what you've tried, and any specific challenges. WARNING: Large inline code must NOT be shared in prompt. Provide full-path to files on disk as separate parameter.
`working_directory_absolute_path`	`string`	Absolute path to an existing directory where generated code artifacts can be saved.
`absolute_file_paths`	`array` optional	Full, absolute file paths to relevant code in order to share with external model
`continuation_id`	`string` optional	Unique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.
`images`	`array` optional	Image paths (absolute) or base64 strings for optional visual context.
`temperature`	`number` optional	0 = deterministic · 1 = creative.
`thinking_mode`	`string` optional	Reasoning depth: minimal, low, medium, high, or max.

Tool: clink

Link a request to an external AI CLI (Gemini CLI, Qwen CLI, etc.) through PAL MCP to reuse their capabilities inside existing workflows.

Parameters	Type	Description
`cli_name`	`string`	Configured CLI client name (from conf/cli_clients). Available: claude, codex, gemini
`prompt`	`string`	User request forwarded to the CLI (conversation context is pre-applied).
`absolute_file_paths`	`array` optional	Full paths to relevant code
`continuation_id`	`string` optional	Unique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.
`images`	`array` optional	Optional absolute image paths or base64 blobs for visual context.
`role`	`string` optional	Optional role preset defined for the selected CLI (defaults to 'default'). Roles per CLI: claude: codereviewer, default, planner; codex: codereviewer, default, planner; gemini: codereviewer, default, planner

This tool is read-only. It does not modify its environment.

Tool: codereview

Performs systematic, step-by-step code review with expert validation. Use for comprehensive analysis covering quality, security, performance, and architecture. Guides through structured investigation to ensure thoroughness.

Parameters	Type	Description
`findings`	`string`	Capture findings (positive and negative) across quality, security, performance, and architecture; update each step.
`model`	`string`	Currently in auto model selection mode. CRITICAL: When the user names a model, you MUST use that exact name unless the server rejects it. If no model is provided, you may use the `listmodels` tool to review options and select an appropriate match. Top models: gpt-5.2 (score 100, 400K ctx, thinking, code-gen); gpt-5.1-codex (score 100, 400K ctx, thinking, code-gen); gemini-2.5-pro (score 100, 1.0M ctx, thinking, code-gen); gemini-3-pro-preview (score 100, 1.0M ctx, thinking, code-gen); gpt-5.2-pro (score 100, 400K ctx, thinking, code-gen); +26 more via `listmodels`.
`next_step_required`	`boolean`	True when another review step follows. External validation: step 1 → True, step 2 → False. Internal validation: set False immediately. Apply the same rule on continuation flows.
`step`	`string`	Review narrative. Step 1: outline the review strategy. Later steps: report findings. MUST cover quality, security, performance, and architecture. Reference code via `relevant_files`; avoid dumping large snippets.
`step_number`	`integer`	Current review step (starts at 1) – each step should build on the last.
`total_steps`	`integer`	Number of review steps planned. External validation: two steps (analysis + summary). Internal validation: one step. Use the same limits when continuing an existing review via continuation_id.
`confidence`	`string` optional	Confidence level: exploring (just starting), low (early investigation), medium (some evidence), high (strong evidence), very_high (comprehensive understanding), almost_certain (near complete confidence), certain (100% confidence locally - no external validation needed)
`continuation_id`	`string` optional	Unique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.
`files_checked`	`array` optional	Absolute paths of every file reviewed, including those ruled out.
`focus_on`	`string` optional	Optional note on areas to emphasise (e.g. 'threading', 'auth flow').
`hypothesis`	`string` optional	Current theory about issue/goal based on work
`images`	`array` optional	Optional diagram or screenshot paths that clarify review context.
`issues_found`	`array` optional	Issues with severity (critical/high/medium/low) and descriptions.
`relevant_context`	`array` optional	Methods/functions identified as involved in the issue
`relevant_files`	`array` optional	Step 1: list all files/dirs under review. Must be absolute full non-abbreviated paths. Final step: narrow to files tied to key findings.
`review_type`	`string` optional	Review focus: full, security, performance, or quick.
`review_validation_type`	`string` optional	Set 'external' (default) for expert follow-up or 'internal' for local-only review.
`severity_filter`	`string` optional	Lowest severity to include when reporting issues (critical/high/medium/low/all).
`standards`	`string` optional	Coding standards or style guides to enforce.
`temperature`	`number` optional	0 = deterministic · 1 = creative.
`thinking_mode`	`string` optional	Reasoning depth: minimal, low, medium, high, or max.
`use_assistant_model`	`boolean` optional	Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

This tool is read-only. It does not modify its environment.

Tool: consensus

Builds multi-model consensus through systematic analysis and structured debate. Use for complex decisions, architectural choices, feature proposals, and technology evaluations. Consults multiple models with different stances to synthesize comprehensive recommendations.

Parameters	Type	Description
`findings`	`string`	Step 1: your independent analysis for later synthesis (not shared with other models). Steps 2+: summarize the newest model response.
`next_step_required`	`boolean`	True if more model consultations remain; set false when ready to synthesize.
`step`	`string`	Consensus prompt. Step 1: write the exact proposal/question every model will see (use 'Evaluate…', not meta commentary). Steps 2+: capture internal notes about the latest model response—these notes are NOT sent to other models.
`step_number`	`integer`	Current step index (starts at 1). Step 1 is your analysis; steps 2+ handle each model response.
`total_steps`	`integer`	Total steps = number of models consulted plus the final synthesis step.
`continuation_id`	`string` optional	Unique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.
`current_model_index`	`integer` optional	0-based index of the next model to consult (managed internally).
`images`	`array` optional	Optional absolute image paths or base64 references that add helpful visual context.
`model_responses`	`array` optional	Internal log of responses gathered so far.
`models`	`array` optional	User-specified roster of models to consult (provide at least two entries). User-specified list of models to consult (provide at least two entries). Each entry may include model, stance (for/against/neutral), and stance_prompt. Each (model, stance) pair must be unique, e.g. [{'model':'gpt5','stance':'for'}, {'model':'pro','stance':'against'}]. When the user names a model, you MUST use that exact value or report the provider error—never swap in another option. Use the `listmodels` tool for the full roster. Top models: gpt-5.2 (score 100, 400K ctx, thinking, code-gen); gpt-5.1-codex (score 100, 400K ctx, thinking, code-gen); gemini-2.5-pro (score 100, 1.0M ctx, thinking, code-gen); gemini-3-pro-preview (score 100, 1.0M ctx, thinking, code-gen); gpt-5.2-pro (score 100, 400K ctx, thinking, code-gen); +26 more via `listmodels`.
`relevant_files`	`array` optional	Optional supporting files that help the consensus analysis. Must be absolute full, non-abbreviated paths.
`use_assistant_model`	`boolean` optional	Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

This tool is read-only. It does not modify its environment.

Tool: debug

Performs systematic debugging and root cause analysis for any type of issue. Use for complex bugs, mysterious errors, performance issues, race conditions, memory leaks, and integration problems. Guides through structured investigation with hypothesis testing and expert analysis.

Parameters	Type	Description
`findings`	`string`	Discoveries: clues, code/log evidence, disproven theories. Be specific. If no bug found, document clearly as valid.
`model`	`string`	Currently in auto model selection mode. CRITICAL: When the user names a model, you MUST use that exact name unless the server rejects it. If no model is provided, you may use the `listmodels` tool to review options and select an appropriate match. Top models: gpt-5.2 (score 100, 400K ctx, thinking, code-gen); gpt-5.1-codex (score 100, 400K ctx, thinking, code-gen); gemini-2.5-pro (score 100, 1.0M ctx, thinking, code-gen); gemini-3-pro-preview (score 100, 1.0M ctx, thinking, code-gen); gpt-5.2-pro (score 100, 400K ctx, thinking, code-gen); +26 more via `listmodels`.
`next_step_required`	`boolean`	True if you plan to continue the investigation with another step. False means root cause is known or investigation is complete. IMPORTANT: When continuation_id is provided (continuing a previous conversation), set this to False to immediately proceed with expert analysis.
`step`	`string`	Investigation step. Step 1: State issue+direction. Symptoms misleading; 'no bug' valid. Trace dependencies, verify hypotheses. Use relevant_files for code; this for text only.
`step_number`	`integer`	Current step index (starts at 1). Build upon previous steps.
`total_steps`	`integer`	Estimated total steps needed to complete the investigation. Adjust as new findings emerge. IMPORTANT: When continuation_id is provided (continuing a previous conversation), set this to 1 as we're not starting a new multi-step investigation.
`confidence`	`string` optional	Your confidence in the hypothesis: exploring (starting out), low (early idea), medium (some evidence), high (strong evidence), very_high (very strong evidence), almost_certain (nearly confirmed), certain (100% confidence - root cause and fix are both confirmed locally with no need for external validation). WARNING: Do NOT use 'certain' unless the issue can be fully resolved with a fix, use 'very_high' or 'almost_certain' instead when not 100% sure. Using 'certain' means you have ABSOLUTE confidence locally and PREVENTS external model validation.
`continuation_id`	`string` optional	Unique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.
`files_checked`	`array` optional	All examined files (absolute paths), including ruled-out ones.
`hypothesis`	`string` optional	Concrete root cause theory from evidence. Can revise. Valid: 'No bug found - user misunderstanding' or 'Symptoms unrelated to code' if supported.
`images`	`array` optional	Optional screenshots/visuals clarifying issue (absolute paths).
`issues_found`	`array` optional	Issues identified with severity levels during work
`relevant_context`	`array` optional	Methods/functions identified as involved in the issue
`relevant_files`	`array` optional	Files directly relevant to issue (absolute paths). Cause, trigger, or manifestation locations.
`temperature`	`number` optional	0 = deterministic · 1 = creative.
`thinking_mode`	`string` optional	Reasoning depth: minimal, low, medium, high, or max.
`use_assistant_model`	`boolean` optional	Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

This tool is read-only. It does not modify its environment.

Tool: docgen

Generates comprehensive code documentation with systematic analysis of functions, classes, and complexity. Use for documentation generation, code analysis, complexity assessment, and API documentation. Analyzes code structure and patterns to create thorough documentation.

Parameters	Type	Description
`comments_on_complex_logic`	`boolean`	True (default) to add inline comments around non-obvious logic.
`document_complexity`	`boolean`	Include algorithmic complexity (Big O) analysis when True (default).
`document_flow`	`boolean`	Include call flow/dependency notes when True (default).
`findings`	`string`	Important findings, evidence and insights discovered in this step
`next_step_required`	`boolean`	Whether another work step is needed. When false, aim to reduce total_steps to match step_number to avoid mismatch.
`num_files_documented`	`integer`	Count of files finished so far. Increment only when a file is fully documented.
`step`	`string`	Current work step content and findings from your overall work
`step_number`	`integer`	Current step number in work sequence (starts at 1)
`total_files_to_document`	`integer`	Total files identified in discovery; completion requires matching this count.
`total_steps`	`integer`	Estimated total steps needed to complete work
`update_existing`	`boolean`	True (default) to polish inaccurate or outdated docs instead of leaving them untouched.
`continuation_id`	`string` optional	Unique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.
`issues_found`	`array` optional	Issues identified with severity levels during work
`relevant_context`	`array` optional	Methods/functions identified as involved in the issue
`relevant_files`	`array` optional	Files identified as relevant to issue/goal (FULL absolute paths to real files/folders - DO NOT SHORTEN)
`use_assistant_model`	`boolean` optional	Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

This tool is read-only. It does not modify its environment.

Tool: listmodels

Shows which AI model providers are configured, available model names, their aliases and capabilities.

Tool: planner

Breaks down complex tasks through interactive, sequential planning with revision and branching capabilities. Use for complex project planning, system design, migration strategies, and architectural decisions. Builds plans incrementally with deep reflection for complex scenarios.

Parameters	Type	Description
`model`

[...]

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Details

Docker Image

https://hub.docker.com/repository/docker/mcp/zen

Author

https://github.com/BeehiveInnovations

Repository

https://github.com/beehiveinnovations/zen-mcp-server

Attribute

Details

Dockerfile

https://github.com/beehiveinnovations/zen-mcp-server/blob/7afc7c1cc96e23992c8f105f960132c657883bb1/Dockerfile

Commit

7afc7c1cc96e23992c8f105f960132c657883bb1

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Tools provided by this Server

Short Description

analyze

Performs comprehensive code analysis with systematic investigation and expert validation.

apilookup

Use this tool automatically when you need current API/SDK documentation, latest version info, breaking changes, deprecations, migration guides, or official release notes.

challenge

Prevents reflexive agreement by forcing critical thinking and reasoned analysis when a statement is challenged.

chat

General chat and collaborative thinking partner for brainstorming, development discussion, getting second opinions, and exploring ideas.

clink

Link a request to an external AI CLI (Gemini CLI, Qwen CLI, etc.) through PAL MCP to reuse their capabilities inside existing workflows.

codereview

Performs systematic, step-by-step code review with expert validation.

consensus

Builds multi-model consensus through systematic analysis and structured debate.

debug

Performs systematic debugging and root cause analysis for any type of issue.

docgen

Generates comprehensive code documentation with systematic analysis of functions, classes, and complexity.

listmodels

Shows which AI model providers are configured, available model names, their aliases and capabilities.

planner

Breaks down complex tasks through interactive, sequential planning with revision and branching capabilities.

precommit

Validates git changes and repository state before committing with systematic analysis.

refactor

Analyzes code for refactoring opportunities with systematic investigation.

secaudit

Performs comprehensive security audit with systematic vulnerability assessment.

testgen

Creates comprehensive test suites with edge case coverage for specific functions, classes, or modules.

thinkdeep

Performs multi-stage investigation and reasoning for complex problem analysis.

tracer

Performs systematic code tracing with modes for execution flow or dependency mapping.

version

Get server version, configuration details, and list of available tools.

Parameters

Type

Description

findings

string

Summary of discoveries from this step, including architectural patterns, tech stack assessment, scalability characteristics, performance implications, maintainability factors, and strategic improvement opportunities. IMPORTANT: Document both strengths (good patterns, solid architecture) and concerns (tech debt, overengineering, unnecessary complexity). In later steps, confirm or update past findings with additional evidence.

model

string

Currently in auto model selection mode. CRITICAL: When the user names a model, you MUST use that exact name unless the server rejects it. If no model is provided, you may use the listmodels tool to review options and select an appropriate match. Top models: gpt-5.2 (score 100, 400K ctx, thinking, code-gen); gpt-5.1-codex (score 100, 400K ctx, thinking, code-gen); gemini-2.5-pro (score 100, 1.0M ctx, thinking, code-gen); gemini-3-pro-preview (score 100, 1.0M ctx, thinking, code-gen); gpt-5.2-pro (score 100, 400K ctx, thinking, code-gen); +26 more via listmodels.

next_step_required

boolean

Set to true if you plan to continue the investigation with another step. False means you believe the analysis is complete and ready for expert validation.

step

string

The analysis plan. Step 1: State your strategy, including how you will map the codebase structure, understand business logic, and assess code quality, performance implications, and architectural patterns. Later steps: Report findings and adapt the approach as new insights emerge.

step_number

integer

The index of the current step in the analysis sequence, beginning at 1. Each step should build upon or revise the previous one.

total_steps

integer

Your current estimate for how many steps will be needed to complete the analysis. Adjust as new findings emerge.

analysis_type

string optional

Type of analysis to perform (architecture, performance, security, quality, general)

confidence

string optional

Your confidence in the analysis: exploring, low, medium, high, very_high, almost_certain, or certain. 'certain' indicates the analysis is complete and ready for validation.

continuation_id

string optional

Unique thread continuation ID for multi-turn conversations. Works across different tools. ALWAYS reuse the last continuation_id you were given—this preserves full conversation context, files, and findings so the agent can resume seamlessly.

files_checked

array optional

List all files examined (absolute paths). Include even ruled-out files to track exploration path.

images

array optional

Optional absolute paths to architecture diagrams or visual references that help with analysis context.

issues_found

array optional

Issues or concerns identified during analysis, each with severity level (critical, high, medium, low)

output_format

string optional

How to format the output (summary, detailed, actionable)

relevant_context

array optional

Methods/functions identified as involved in the issue

relevant_files

array optional

Subset of files_checked directly relevant to analysis findings (absolute paths). Include files with significant patterns, architectural decisions, or strategic improvement opportunities.

temperature

number optional

0 = deterministic · 1 = creative.

thinking_mode

string optional

Reasoning depth: minimal, low, medium, high, or max.

use_assistant_model

boolean optional

Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

Parameters

Type

Description

prompt

string

The API, SDK, library, framework, or technology you need current documentation, version info, breaking changes, or migration guidance for.

Parameters

Type

Description

prompt

string

Statement to scrutinize. If you invoke challenge manually, strip the word 'challenge' and pass just the statement. Automatic invocations send the full user message as-is; do not modify it.

Parameters

Type

Description

model

string

prompt

string

Your question or idea for collaborative thinking to be sent to the external model. Provide detailed context, including your goal, what you've tried, and any specific challenges. WARNING: Large inline code must NOT be shared in prompt. Provide full-path to files on disk as separate parameter.

working_directory_absolute_path

string

Absolute path to an existing directory where generated code artifacts can be saved.

absolute_file_paths

array optional

Full, absolute file paths to relevant code in order to share with external model

continuation_id

string optional

images

array optional

Image paths (absolute) or base64 strings for optional visual context.

temperature

number optional

0 = deterministic · 1 = creative.

thinking_mode

string optional

Reasoning depth: minimal, low, medium, high, or max.

Parameters

Type

Description

cli_name

string

Configured CLI client name (from conf/cli_clients). Available: claude, codex, gemini

prompt

string

User request forwarded to the CLI (conversation context is pre-applied).

absolute_file_paths

array optional

Full paths to relevant code

continuation_id

string optional

images

array optional

Optional absolute image paths or base64 blobs for visual context.

role

string optional

Optional role preset defined for the selected CLI (defaults to 'default'). Roles per CLI: claude: codereviewer, default, planner; codex: codereviewer, default, planner; gemini: codereviewer, default, planner

Parameters

Type

Description

findings

string

Capture findings (positive and negative) across quality, security, performance, and architecture; update each step.

model

string

next_step_required

boolean

True when another review step follows. External validation: step 1 → True, step 2 → False. Internal validation: set False immediately. Apply the same rule on continuation flows.

step

string

Review narrative. Step 1: outline the review strategy. Later steps: report findings. MUST cover quality, security, performance, and architecture. Reference code via relevant_files; avoid dumping large snippets.

step_number

integer

Current review step (starts at 1) – each step should build on the last.

total_steps

integer

Number of review steps planned. External validation: two steps (analysis + summary). Internal validation: one step. Use the same limits when continuing an existing review via continuation_id.

confidence

string optional

Confidence level: exploring (just starting), low (early investigation), medium (some evidence), high (strong evidence), very_high (comprehensive understanding), almost_certain (near complete confidence), certain (100% confidence locally - no external validation needed)

continuation_id

string optional

files_checked

array optional

Absolute paths of every file reviewed, including those ruled out.

focus_on

string optional

Optional note on areas to emphasise (e.g. 'threading', 'auth flow').

hypothesis

string optional

Current theory about issue/goal based on work

images

array optional

Optional diagram or screenshot paths that clarify review context.

issues_found

array optional

Issues with severity (critical/high/medium/low) and descriptions.

relevant_context

array optional

Methods/functions identified as involved in the issue

relevant_files

array optional

Step 1: list all files/dirs under review. Must be absolute full non-abbreviated paths. Final step: narrow to files tied to key findings.

review_type

string optional

Review focus: full, security, performance, or quick.

review_validation_type

string optional

Set 'external' (default) for expert follow-up or 'internal' for local-only review.

severity_filter

string optional

Lowest severity to include when reporting issues (critical/high/medium/low/all).

standards

string optional

Coding standards or style guides to enforce.

temperature

number optional

0 = deterministic · 1 = creative.

thinking_mode

string optional

Reasoning depth: minimal, low, medium, high, or max.

use_assistant_model

boolean optional

Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

Parameters

Type

Description

findings

string

Step 1: your independent analysis for later synthesis (not shared with other models). Steps 2+: summarize the newest model response.

next_step_required

boolean

True if more model consultations remain; set false when ready to synthesize.

step

string

Consensus prompt. Step 1: write the exact proposal/question every model will see (use 'Evaluate…', not meta commentary). Steps 2+: capture internal notes about the latest model response—these notes are NOT sent to other models.

step_number

integer

Current step index (starts at 1). Step 1 is your analysis; steps 2+ handle each model response.

total_steps

integer

Total steps = number of models consulted plus the final synthesis step.

continuation_id

string optional

current_model_index

integer optional

0-based index of the next model to consult (managed internally).

images

array optional

Optional absolute image paths or base64 references that add helpful visual context.

model_responses

array optional

Internal log of responses gathered so far.

models

array optional

User-specified roster of models to consult (provide at least two entries). User-specified list of models to consult (provide at least two entries). Each entry may include model, stance (for/against/neutral), and stance_prompt. Each (model, stance) pair must be unique, e.g. [{'model':'gpt5','stance':'for'}, {'model':'pro','stance':'against'}]. When the user names a model, you MUST use that exact value or report the provider error—never swap in another option. Use the listmodels tool for the full roster. Top models: gpt-5.2 (score 100, 400K ctx, thinking, code-gen); gpt-5.1-codex (score 100, 400K ctx, thinking, code-gen); gemini-2.5-pro (score 100, 1.0M ctx, thinking, code-gen); gemini-3-pro-preview (score 100, 1.0M ctx, thinking, code-gen); gpt-5.2-pro (score 100, 400K ctx, thinking, code-gen); +26 more via listmodels.

relevant_files

array optional

Optional supporting files that help the consensus analysis. Must be absolute full, non-abbreviated paths.

use_assistant_model

boolean optional

Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

Parameters

Type

Description

findings

string

Discoveries: clues, code/log evidence, disproven theories. Be specific. If no bug found, document clearly as valid.

model

string

next_step_required

boolean

True if you plan to continue the investigation with another step. False means root cause is known or investigation is complete. IMPORTANT: When continuation_id is provided (continuing a previous conversation), set this to False to immediately proceed with expert analysis.

step

string

Investigation step. Step 1: State issue+direction. Symptoms misleading; 'no bug' valid. Trace dependencies, verify hypotheses. Use relevant_files for code; this for text only.

step_number

integer

Current step index (starts at 1). Build upon previous steps.

total_steps

integer

Estimated total steps needed to complete the investigation. Adjust as new findings emerge. IMPORTANT: When continuation_id is provided (continuing a previous conversation), set this to 1 as we're not starting a new multi-step investigation.

confidence

string optional

Your confidence in the hypothesis: exploring (starting out), low (early idea), medium (some evidence), high (strong evidence), very_high (very strong evidence), almost_certain (nearly confirmed), certain (100% confidence - root cause and fix are both confirmed locally with no need for external validation). WARNING: Do NOT use 'certain' unless the issue can be fully resolved with a fix, use 'very_high' or 'almost_certain' instead when not 100% sure. Using 'certain' means you have ABSOLUTE confidence locally and PREVENTS external model validation.

continuation_id

string optional

files_checked

array optional

All examined files (absolute paths), including ruled-out ones.

hypothesis

string optional

Concrete root cause theory from evidence. Can revise. Valid: 'No bug found - user misunderstanding' or 'Symptoms unrelated to code' if supported.

images

array optional

Optional screenshots/visuals clarifying issue (absolute paths).

issues_found

array optional

Issues identified with severity levels during work

relevant_context

array optional

Methods/functions identified as involved in the issue

relevant_files

array optional

Files directly relevant to issue (absolute paths). Cause, trigger, or manifestation locations.

temperature

number optional

0 = deterministic · 1 = creative.

thinking_mode

string optional

Reasoning depth: minimal, low, medium, high, or max.

use_assistant_model

boolean optional

Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

Parameters

Type

Description

comments_on_complex_logic

boolean

True (default) to add inline comments around non-obvious logic.

document_complexity

boolean

Include algorithmic complexity (Big O) analysis when True (default).

document_flow

boolean

Include call flow/dependency notes when True (default).

findings

string

Important findings, evidence and insights discovered in this step

next_step_required

boolean

Whether another work step is needed. When false, aim to reduce total_steps to match step_number to avoid mismatch.

num_files_documented

integer

Count of files finished so far. Increment only when a file is fully documented.

step

string

Current work step content and findings from your overall work

step_number

integer

Current step number in work sequence (starts at 1)

total_files_to_document

integer

Total files identified in discovery; completion requires matching this count.

total_steps

integer

Estimated total steps needed to complete work

update_existing

boolean

True (default) to polish inaccurate or outdated docs instead of leaving them untouched.

continuation_id

string optional

issues_found

array optional

Issues identified with severity levels during work

relevant_context

array optional

Methods/functions identified as involved in the issue

relevant_files

array optional

Files identified as relevant to issue/goal (FULL absolute paths to real files/folders - DO NOT SHORTEN)

use_assistant_model

boolean optional

Use assistant model for expert analysis after workflow steps. False skips expert analysis, relies solely on your personal investigation. Defaults to True for comprehensive validation.

Parameters

Type

Description

model

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