model-council-mcp

Server Quality Checklist

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Latest release: v0.2.79
Disambiguation5/5
Each tool targets a distinct operation: model discovery, configuration updates, synchronous query, async query, result retrieval, config retrieval, environment status, initial setup, and timeout management. The only potential overlap between setup_council and configure_council is clearly differentiated by their descriptions (tiers vs. council composition).
Naming Consistency4/5
Tools follow a consistent snake_case convention with mostly verb_noun patterns (list_models, ask_council, get_council_config). Minor deviations like council_status (noun_noun) and setup_council (compound verb) are still predictable and do not hinder usability.
Tool Count5/5
At 9 tools, the server is well-scoped for a model council management domain. Each tool earns its place, covering discovery, setup, configuration, querying, and maintenance without unnecessary bloat.
Completeness5/5
The tool set covers the full lifecycle: listing models, setting up with tiers, fine-tuning configuration, synchronous and asynchronous ask, result retrieval, config/status readouts, and timeout adjustment. No critical gaps or dead ends are apparent.
Average 4.3/5 across 9 of 9 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 127 commits in the last 12 weeks
- Last stable release on August 4, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under Apache 2.0.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, so mutation is known. The description adds valuable behavioral context: 'Choices persist across reloads' and 'registering a NEW subscription provider or changing concurrency takes full effect after a reload.' This discloses persistence and side-effect timing beyond what the annotation conveys.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded: a clear action sentence, a brief contextual explanation, and an important caveat. Every sentence earns its place with no fluff or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description adequately covers the tool's behavior, side effects, and persistence. It doesn't describe return values, but that may be covered by siblings like 'get_council_config'. The reload note addresses a critical operational detail, making it sufficiently complete for a setup tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with each parameter described and enum values provided. The description adds semantic meaning by explaining that 'Tiers gate cloud availability and per-provider concurrency,' which is not in the schema. It repeats enum lists but ties them to the higher-level purpose.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb+resource: 'Set subscription tiers, then re-detect and auto-populate the council.' It also specifies the exact tiers for each provider, giving strong scope. However, it does not explicitly distinguish itself from the sibling 'configure_council', which could be confused for similar functionality.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context implies this is for initial setup ('Set subscription tiers, then re-detect and auto-populate'), and the note about persistence and reload provides situational guidance. However, it does not explicitly state when to use this vs alternatives like 'configure_council', nor does it specify exclusions or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=false, so the mutation aspect is known. The description adds valuable behavioral context: changes persist across restarts/reloads and fields not supplied are left untouched, which goes beyond what annotations provide. It does not mention potential side effects, but for a config update tool this is sufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and front-loaded with the core action ('Update the council configuration'). The second sentence efficiently conveys persistence and partial-update semantics. No redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential contextual points: what the tool does, persistence behavior, and partial updates. Given the tool's moderate complexity and thorough schema descriptions, it is complete enough. It does not describe return values, but no output schema exists and this is a config update where return format is less critical.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with rich descriptions for all six parameters, so the baseline is 3. The tool description only lists parameter names without adding syntax or semantics beyond the schema, relying on the schema to carry the detail.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Update the council configuration' and enumerates the specific aspects it controls (models, judge model, response mode, max deconfliction rounds). It distinguishes from siblings by focusing on updates and referencing setup_council's persistence behavior, making its role unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for updating an existing council configuration, but it does not explicitly state when to use this tool versus setup_council or set_council_timeouts. The reference to setup_council's tier choices provides a comparison but no direct 'when to use / when not to use' guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations indicate readOnlyHint=true, so the read-only nature is already disclosed. The description adds useful context about aggregating all providers and the intended use with configure_council, but does not go beyond that to describe return format or any behavioral quirks.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences, front-loading the core purpose and then providing a practical directive. The provider enumeration is verbose but informative and earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool with full schema coverage and annotations, the description sufficiently explains what the tool does, the scope of providers, and how to use the results. No output schema exists, but the description covers the essential return value usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the filter_provider parameter is fully documented. The description does not add additional parameter-specific meaning beyond what the schema already provides, but it correctly implies the returned model IDs are for passing to configure_council.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists all AI models across every configured provider, enumerating specific providers. This distinguishes it from sibling tools like configure_council or ask_council, which serve different functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly ties usage to configure_council by saying 'Use the returned model IDs when calling configure_council.' This gives clear context for when to use it, though it does not explicitly state when not to use it or mention alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (which only provide readOnlyHint=false), the description discloses important behavioral details: the run happens in the background, a job_id is returned immediately, and jobs are in-memory and do not survive a server reload. It also directs the user to the polling tool. This goes beyond the minimal annotation signal and gives useful operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is only three sentences, front-loaded with the core purpose, and every sentence adds value: the first defines the behavior, the second covers inputs and result retrieval, and the third notes the in-memory limitation. No redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For an async background tool with 11 parameters and no output schema, the description covers the essential workflow: starting a job, returning a job_id immediately, polling for results, and the job's in-memory persistence limitation. It could specify the job_id response shape, but the polling instruction makes the flow clear enough for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with per-parameter descriptions, so the schema already explains each parameter. The description adds that inputs are the same as ask_council, which is helpful for transfer but does not significantly enhance meaning beyond what the schema provides. Baseline 3 is appropriate here.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function with a specific verb and resource: 'Start a council run in the background and return a job_id immediately.' It also distinguishes itself from the synchronous sibling ask_council by emphasizing the non-blocking nature for long deconfliction/dialectic runs or slow local models.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use this tool (when a run might block) and instructs the user to poll get_council_result with the job_id. It references ask_council for shared inputs but does not explicitly state a 'when not to use' scenario or name an alternative for synchronous needs, which would merit a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Even with readOnlyHint=true, the description adds meaningful behavioral detail: it explains the status values (running/done/error) and that the full result is returned when done. It also clarifies that list=true returns metadata only, which goes beyond the basic read-only annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the main purpose, and each clause adds actionable information without waste. It is concise yet complete for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description provides essential behavioral details about statuses and listing. It could optionally mention error handling specifics, but for a low-complexity tool with two parameters, this is sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema already describes both parameters at 100% coverage, the description clarifies the relationship between them: job_id for fetching vs. omitting or setting list=true for listing. This adds practical semantics about how the parameters interact.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches a background council run started with ask_council_async, using a specific verb ('Fetch') and resource. It also distinguishes from siblings by mentioning the async context and the ability to list recent jobs.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly describes when to pass job_id versus when to omit it or set list=true, giving clear usage conditions. It doesn't explicitly name alternatives like ask_council for sync, but the context is evident from sibling tool names.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description does not need to state safety. It adds useful behavioral context beyond the annotation: it reports detection results, mentions that Grok CLI is 'fail-closed', and notes universal compatibility across clients and install methods. This is valuable and non-redundant context, justifying a 4.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, with the main verb and purpose in the first phrase. Every following item is a concrete detail that adds value, and no information is redundant or wasted. It is well-structured, front-loaded, and appropriately sized for a status readout tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, read-only status tool with no output schema, the description covers the full scope of what the tool reports and explicitly states its universal compatibility. It does not need to explain return values or parameters, and it does not omit any obvious aspect that an agent would need to decide to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty with 100% coverage. The description therefore has no parameter burden to carry. The baseline for zero-parameter tools is 4, and the description does not need to explain or document parameters, making this score appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Report') and resource ('detected environment and current setup'), then enumerates concrete items it covers (Ollama models, cloud reachability, login states, Grok CLI, council members, tiers, concurrency, quota). This clearly distinguishes it from sibling tools like list_models or get_council_config, which are more targeted.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: 'Use this as the welcome/status readout — it works in every client and install method.' This tells when to use it, but it does not explicitly mention when not to use it or name alternative tools for specific checks. Since the context is clear and the instruction is direct, it earns a 4.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotation readOnlyHint=true already signals a safe read operation, and the description aligns with this by using 'Return'. It adds value by disclosing the specific configuration fields returned, which is helpful for the agent without contradicting the annotation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single well-structured sentence that front-loads the action ('Return') and lists the key configuration attributes with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there are no parameters and no output schema, the description adequately communicates the purpose and return content. It is complete for a simple read-only getter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With zero parameters, the baseline is 4. The description does not need to explain parameters, and it meaningfully describes the output structure, which is useful given there is no output schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Return' with the resource 'current council configuration' and enumerates the exact fields (member models, judge model, response mode, max deconfliction rounds). This clearly distinguishes it from siblings like configure_council or list_models, which have different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly implies usage as a read-only getter for the current configuration state, and the sibling tool names reinforce the distinction from mutation tools. However, it does not explicitly state when not to use it or name alternatives, so it stops short of a full 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite sparse annotations (only readOnlyHint=false), the description thoroughly discloses behavioral traits: the deconfliction loop and 0-100% score, vision member auto-detection and skipping, local git diff execution, full_repo_access safety warnings including codex-cli's non-confined read behavior, and reasoning_effort cost/clamping across rounds. This far exceeds annotation coverage and gives the agent a clear safety and side-effect picture.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is long but information-dense, with each sentence serving a purpose: modes, vision behavior, git diff usage, full_repo_access warning, reasoning_effort. It is front-loaded with the core action, then details. It could be tightened, but for a tool with 11 parameters and multiple complex modes, the length is justified and well-organized.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is complex and has no output schema, yet the description covers the major behavioral outcomes: structured response, deconfliction score, visionRouting in results, verbose per-round details, and raw member responses. It does not fully describe the complete response envelope, but it provides enough context for an agent to invoke correctly and interpret core results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the baseline is 3, but the description adds substantial meaning beyond the schema. It elaborates each mode into full operational semantics, explains the visionRouting effect for images, provides detailed git_ref value examples, and warns about full_repo_access enforcement differences per provider. This transforms bare parameter names into actionable usage knowledge.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a clear, specific verb+resource statement: 'Send a question to the model council and get a structured response.' It then enumerates distinct modes (individual, categorized, deconflicted, pooled, dialectic) and special use cases like image questions and repo review, making the tool's scope unambiguous and clearly distinguishing it from siblings like list_models and get_council_result.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides concrete guidance on when to use specific features: use git_ref for repo diffs, full_repo_access for repo-wide reviews, and images for vision questions. It explains mode selection in detail. However, it does not explicitly contrast itself with ask_council_async or other sibling tools, so usage-vs-alternative guidance is incomplete.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the readOnlyHint:false annotation, the description discloses persistence across reloads, overriding env defaults, that no reload is required, that it takes effect on the next ask_council, and that it returns the now-effective values. This fully informs the agent of side effects and state changes.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact yet information-dense, with no redundant phrasing. It front-loads the core purpose and then efficiently covers parameter distinctions, usage guidance, and return value without wasting words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema, the description adequately covers return value, effect timing, parameter conditions, and troubleshooting context. Given the moderate complexity (two optional params), this is complete for an agent to select and invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with detailed parameter descriptions and defaults, so baseline is 3. The description adds meaningful context by mapping each parameter to its triggering condition (text-only vs full_repo_access) and explaining that omitting a parameter leaves it unchanged, which is valuable beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Set the per-completion wall-clock timeouts (ms) for council calls.' It distinguishes this tool from siblings like configure_council by explicitly scoping to timeouts and mentioning persistence and env override behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description directly states when to raise timeouts ('Raise these when a member answer is cut mid-generation') and clarifies when each parameter applies (run_timeout_ms for text-only calls, repo_timeout_ms when full_repo_access is set). It also notes optional omission semantics for leaving values unchanged.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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