rebuild-dossier

Server Quality Checklist

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Latest release: v0.2.2-paper
Disambiguation5/5
Each tool has a clearly distinct role: ingest_repo and crawl_site cover different evidence sources, get_case_queue and resolve_case form a queue-management pair, flag_known_bug records domain knowledge, and generate_spec produces the final output. No pair of tools is likely to be confused because their purposes and side effects are cleanly separated.
Naming Consistency5/5
All six tools follow the same verb_noun snake_case convention with clear action verbs: ingest, crawl, flag, get, resolve, and generate. The naming is consistent and makes the overall pipeline structure readable at a glance.
Tool Count5/5
Six tools is well-scoped for a multi-stage dossier-building pipeline: input collection, a case queue, case resolution, and final generation. Each tool sits at exactly one meaningful stage, so the surface is comprehensive without feeling bloated.
Completeness4/5
The core workflow is well covered: analyze the repo, crawl the site, record known bugs, inspect and resolve ambiguity cases, and generate the rebuild dossier. The main gaps are minor: known bugs can be recorded but not listed, updated, or retracted, and the reconciliation step that populates the case queue is implicit rather than explicitly triggerable.
Average 3.5/5 across 6 of 6 tools scored. Lowest: 2.9/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 88 commits in the last 12 weeks
- Last stable release on August 21, 2026
- 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.
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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries full burden but only states it returns cases. It does not disclose whether the operation is safe, any potential side effects, or the structure of the returned data.
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 a single concise sentence that front-loads the action. While it could benefit from additional detail, it avoids verbosity and is clearly structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity with two parameters and no output schema, the description is minimally adequate. However, it fails to explain what 'unresolved ambiguity cases' are or provide context about the reconciliation domain.
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% and already describes both parameters clearly. The description adds no additional meaning beyond what the schema provides, so baseline score of 3 is appropriate.
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 tool returns unresolved ambiguity cases from reconciliation, using a specific verb and resource. It implicitly distinguishes from sibling tools like resolve_case by being a read operation, but lacks explicit differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus siblings such as resolve_case or generate_spec. There is no mention of prerequisites or context for use.
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, the description carries the burden. It discloses headless execution and periodic progress notifications, but does not mention authorization needs, rate limits, or depth of crawl.
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?
Two sentences, no filler, front-loaded with key action and behavior. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given three parameters, no output schema, and no annotations, the description is too sparse. It omits expected output format, crawling depth, and handling of edge cases.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 67%; 'url' and 'repoPath' are described in schema, but 'maxPages' lacks description. The tool description does not clarify 'maxPages' or add semantic value to any parameter 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 clearly states 'crawl of reachable routes', which is a specific verb and resource. It is distinct from sibling tools that handle cases, specs, and repositories.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like 'ingest_repo' or 'generate_spec'. The description only states what it does without context for appropriate usage.
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?
With no annotations, description carries full burden. It mentions 'No LLM call' which is a useful behavioral trait, but omits details like file system read permissions, potential side effects, or output characteristics.
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?
Single sentence with no filler. Every word is meaningful, clearly stating action and key distinction (no LLM call).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and two parameters, the description is minimally complete but lacks information about return value, error conditions, or how the tool fits into a workflow (e.g., prerequisite for code generation).
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 baseline is 3. Description adds context by listing the files parsed, implying path should point to such a repo, but does not elaborate on parameter formats or constraints beyond 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?
Description clearly states the tool's action: parsing specific files (package.json, configs, routes, tests) via static analysis. It is specific and distinguishes from siblings which involve case management, bug reporting, etc.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does 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 like generate_spec or crawl_site. It does not specify prerequisites or when not to use it.
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, the description must fully disclose behavior. It states the tool resolves a case with human decision, which implies state mutation, but does not detail side effects (e.g., irrevocability, re-opening possibility, or failure conditions). The transparency is functional but incomplete.
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 core functionality, and adds a clarifying property in the second sentence. Every word serves a purpose with no repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema and no annotations, the description covers the main action but lacks details on return values, error handling, or parameter formats (e.g., expected decision string). For a simple action tool it is minimally adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is only 25% (only repoPath has a description). The description adds no new information about parameters like id, decision, or note. It does not explain valid values for 'decision' or the purpose of 'note,' leaving agents to infer from parameter names alone.
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 action ('Resolve one open case with a human decision') and distinguishes itself from siblings by noting its unique availability and lack of elicitation requirement. This makes the tool's purpose immediately understandable and distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description only hints at availability ('Always available, no elicitation capability required') but provides no explicit guidance on when to use this tool versus alternatives like get_case_queue or other siblings. No context on prerequisites or when not to use it.
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?
With no annotations provided, the description carries full burden. It discloses the key behavioral trait that flagging overrides auto-resolve, which is critical for agent decision-making. However, it does not cover other aspects like idempotency, permissions, or reversibility.
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 with two sentences, no fluff. The key action and critical behavioral note are front-loaded.
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 low complexity (2 simple params, no output schema, no annotations), the description covers purpose and a crucial behavioral quirk. However, it lacks context on return value or error handling, which would be helpful for a mutation tool.
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 descriptions for both parameters, so the description adds no additional meaning beyond what the input schema already provides. Baseline score of 3 is 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 'Record a known bug' clearly states the action and resource. The additional sentence about overriding auto-resolve further distinguishes it from sibling tools like resolve_case, implicitly indicating a special behavior.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. It does not mention when not to use or provide context on when flagging a known bug is appropriate compared to other sibling tools.
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?
No annotations are provided, so the description must carry the full behavioral burden, and it does: it states the file-writing side effect, the queue precondition, the optional behavior of the vision classification (sending data to Groq), and the explicit statement that this tool never logs in or handles credentials itself. It also notes the file is gitignored.
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 every sentence carries essential information: the deliverable, the precondition, and two optional behaviors with explicit 'if unset' fallbacks. It is front-loaded with the core action. Slightly dense, but nothing is filler.
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 and two parameters, the description covers prerequisites, side effects, optional features, credential handling, and environment-variable behavior. Nothing an agent needs to decide whether and how to call this tool is missing.
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 baseline is 3. The description adds context about the auth parameter's purpose and behavior, and explains the environment variables, but these are not schema parameters. It doesn't substantially extend the meaning of the two parameters beyond what the schema already provides.
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 states a specific verb ('Write') and lists exactly which files are produced (CLAUDE.md, .claude/, spec/, tests/, and <repo>-rebuild/). This clearly distinguishes it from siblings like ingest_repo or crawl_site, which have different targets and actions.
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 provides an explicit precondition ('Only callable once the case queue is empty') and detailed optional triggers (vision classification env vars, auth storage state) with when-to-use guidance. It doesn't explicitly contrast with sibling tools, but the queue-empty condition and the unique output files make the intended context clear.
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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