chrysalide-mcp
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation5/5
Each tool targets a distinct action: start a job, check status, cancel a job, and fetch the report. The lifecycle states are clearly enumerated in descriptions (running, finished, cancelled), leaving no ambiguity about which tool to call at any point.
Naming Consistency5/5All tools follow a consistent verb_noun pattern with a uniform prefix (chrysalide_get_status, chrysalide_get_report, chrysalide_cancel_task, chrysalide_start_task). Verbs are all action-oriented and snake_case is used consistently throughout.
Tool Count4/5Four tools is a reasonable, focused set for a job-management server covering start, status, report, and cancellation. It's on the smaller end but each tool earns its place and the scope is appropriately narrow.
Completeness4/5The job lifecycle is well covered: start, poll status, retrieve report, and cancel. A possible gap is the lack of a way to list historical jobs or re-fetch past reports, but the core lifecycle has no dead ends.
Average 3.3/5 across 4 of 4 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 9 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
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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
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It discloses the non-blocking behavior ('Non-bloquant') which is useful. However, it doesn't clarify what states can be returned, whether status represents a failure/pending/completed state, or what happens if the job_id is invalid.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely brief — one short sentence. This is appropriately concise for a simple status check tool with one parameter. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There's no output schema and only one parameter. For a simple status polling tool, the description is somewhat thin — it doesn't explain the possible return states, whether the call can block under any condition, or how polling semantics work. Given no annotations and no output schema, more could be provided.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents the job_id parameter as 'L'identifiant du job'. The description adds no additional meaning about parameter semantics, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the tool returns the current status of a job, with a clear verb-resource ('Retourne l'état courant d'un job'). It doesn't explicitly distinguish it from siblings like chrysalide_get_report, but the resource (status vs report) is implied. Non-bloquant clarifies the non-blocking nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. It doesn't explain when a user would want the job status versus getting a report or cancelling/starting a task. The 'Non-bloquant' note hints at use context (async polling) but no explicit when/when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses that the call returns immediately with a job_id (valuable), but does not disclose that the task runs asynchronously in the background, that follow-ups via chrysalide_get_status/get_report are necessary, that a sandbox/worktree is created (implied by worktree param), or any resource/side-effect implications. For a long-running async job launcher, this is a significant gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core purpose. Zero waste. Could arguably add more behavioral detail, but as written it is efficient and readable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite high schema coverage, this is a complex async job launcher with 9 parameters, no output schema, and no annotations. The description doesn't explain the job lifecycle (that it runs in background, needs polled status, could be cancelled via sibling), return format beyond job_id, or relationship to the sibling workflow. For a tool initiating long-running work, more operational context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema already documents all 9 parameters. The description adds minimal parameter meaning beyond this — 'goal' and 'repo_path' are intuitive and reinforced, but nothing about the budget semantics, provider format, or constraints is elaborated in the description. Baseline 3 is appropriate since schema handles the load.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb (Démarre/démarre), the resource (nouveau job Chrysalide), and the key behavior (returns immediately with a job_id). It's clearly distinct from siblings which get status, reports, or cancel. While it doesn't name the siblings, the immediate-return behavior and job_id clearly differentiate it from what siblings do.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context ('Démarre un nouveau job') and the immediate-return behavior implicitly tells the agent not to wait for results, but it doesn't explicitly state when to use this vs alternatives, nor does it mention that follow-up status/report calls would be needed. There's no explicit when/when-not guidance, only implied.
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?
With no annotations provided, the description carries the burden. It adds useful context that the sandbox is preserved for inspection ('La sandbox est conservée pour inspection'), which is a meaningful behavioral disclosure. However, it doesn't state whether cancellation is reversible, what state the job transitions to, or whether results are discarded. Some value added, but gaps remain.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, zero waste. The first states the core action, the second adds a valuable behavioral detail about the sandbox. Efficient and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This is a simple cancellation tool with only 2 params, full schema coverage, and no output schema, so its informational needs are modest. The description covers the core action and a key behavioral detail (sandbox preservation). It's adequate for a task of this simplicity, though it could mention what the cancellation returns or what state the job ends in.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (both params documented: job_id as job identifier, reason as cancellation rationale). The description itself adds no parameter-specific detail beyond the schema, so with full coverage the baseline of 3 applies. The 'reason' param's optional nature and purpose is clear from schema alone.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb+resource: 'Annule un job en cours' (cancels an in-progress job), differentiated from siblings by the action of cancellation. It's specific about what it does, though it doesn't explicitly contrast with sibling tools like get_status or start_task, so a small deduction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use guidance is provided. The tool's purpose implies cancellation of a running job, but there's no mention of when cancel is appropriate versus waiting, whether it can only be applied to running jobs, or any relationship to sibling tools. Usage context is only implied by the name and description.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It warns the report is final and should only be fetched when complete, but doesn't disclose what happens if called early, range of formats, or the structure of the returned report. For a tool returning a 'report final' with no output schema, more behavioral context would be valuable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two short, purposeful sentences with zero wasted words. The critical usage constraint is front-loaded in the second sentence, making it highly scannable. Ideal length for this tool's simplicity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (2 params, no output schema) and the description covers the essential timing condition. However, with no output schema and no annotations, the description doesn't describe the report's content/structure, and it doesn't explain what happens if called before job completion — leaving some ambiguity for a tool that returns a complete report.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so both parameters (format, job_id) are documented in the schema. The description adds no additional parameter detail beyond what the schema provides — baseline 3 is appropriate when the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states the verb+resource ('Retourne le rapport final') and adds a critical usage condition (only when the job is done). It's clear but doesn't explicitly distinguish from siblings beyond the timing constraint.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states when to call: 'À appeler seulement quand le job est terminé.' This is a clear when-to-use condition, and combined with sibling names (get_status, cancel_task, start_task), the agent can infer this is the fetch-results tool distinct from status/control tools.
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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