trm-mcp

by strongtz

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: listing documents, searching with ranking, exact pattern matching, reading page content, rendering images, and comparing documents. There is no ambiguity about which tool to use for a given task.
Naming Consistency4/5
Most tool names are single-word imperative verbs (search, grep, read, render, compare), which is consistent. However, list_documents deviates by using a verb_noun pattern, creating a minor inconsistency.
Tool Count5/5
With 6 tools, the server is well-scoped for document retrieval and inspection. Each tool addresses a distinct aspect of the workflow, and the count feels appropriate for the domain.
Completeness4/5
The toolset covers listing, searching, grep-style extraction, reading, visual rendering, and comparison, which are the core operations for document analysis. Minor gaps might include a dedicated tool for fetching a single document's metadata, but list_documents already provides this.
Average 3.2/5 across 6 of 6 tools scored. Lowest: 2.6/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 4 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

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It adds only 'by page' and 'exact' context, but does not mention read-only nature, pagination, result format, case sensitivity, or document filtering. This is insufficient for safe invocation.
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, efficient sentence with no redundant words. It front-loads the action ('Find') and specifies scope ('by page'), earning its place without excess.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters, no schema descriptions, and no annotations, the description is drastically incomplete. It omits key behavioral details like case sensitivity, result limits, document scoping, and return structure. The presence of an output schema does not compensate for this missing invocation guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It only references 'regex' and indirectly 'pattern', leaving the other three parameters (max_results, document_ids, case_sensitive) unexplained. No parameter-level semantics are provided beyond what the schema titles show.
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 finds exact occurrences of registers, fields, signals, addresses, or regex matches by page, using the specific verb 'Find' with named resource types. It does not explicitly differentiate from the sibling tool 'search', but the 'exact' and 'regex' qualifiers provide enough distinction.
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 is given on when to use grep versus alternatives like 'search'. The description implies exact/regex searching but lacks exclusions or comparisons to sibling tools, leaving the agent to infer appropriate usage.
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?
No annotations are provided, so the description carries the burden. It discloses that the tool performs retrieval with local reranking and returns page citations, which gives some insight into behavior. However, it doesn't explicitly state read-only nature, any limitations, or auth requirements. The description adds some behavioral context but not comprehensive.
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 sentence that conveys the core functionality and key differentiators in a concise, front-loaded manner. No wasted words; every phrase adds meaning.
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 the tool has 4 parameters, no annotations, and no parameter descriptions, the description is too sparse. It doesn't cover scope (e.g., whether it searches all documents), how document_ids affects behavior, or any usage guidance. The output schema exists, so return values are covered, but the tool's context of use is not fully specified.
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 description coverage is 0%, so the description must explain the parameters. It doesn't mention query, top_k, or document_ids. However, it does clarify that 'mode' relates to the hybrid/text/visual options through the description's mention of BM25/dense/visual. Overall, it provides insufficient parameter-level explanation.
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 identifies this as a retrieval tool using hybrid BM25/dense/visual methods, with local reranking and page citations. It distinguishes from sibling tools like grep (which likely does content-based text search) and list_documents (listing) by specifying the retrieval mechanism. However, it uses a noun phrase rather than an explicit verb, but the name 'search' plus description makes the purpose obvious.
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 provides no explicit guidance on when to use this tool versus alternatives like grep, read, or list_documents. It doesn't mention use cases, prerequisites, or exclusions. The technical details imply it's for semantic search, but it doesn't state when to prefer it over grep or other tools.
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?
While annotations are absent, the description adds a useful constraint (up to 20 pages) and lists formats. However, it does not explain indexing, error behavior, or whether results are always read-only (though implied by the name).
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, front-loaded sentence with no filler words, efficiently conveying the core action and options.
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?
For a tool with no annotations, no output schema, and no parameter descriptions, this terse description is insufficient. An agent cannot determine how to specify page ranges or understand return structure, making the tool harder to invoke correctly.
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 description mentions the format options and a page limit, which loosely maps to format and page range parameters, but it does not explain document_id, page_start, or page_end semantics. With 0% schema description coverage, this leaves gaps.
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 reads pages and lists supported output formats, using a specific verb and resource. It does not explicitly distinguish it from sibling tools like render, but its function is reasonably clear.
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 provides no guidance on when to use this tool versus alternatives like search, grep, or render. It does not state prerequisites or typical use cases.
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 of behavioral disclosure. It states it lists documents and specifies output fields, but does not disclose pagination behavior, the effect of the query parameter, or whether it retrieves all documents by default. This provides partial transparency.
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 concise sentence that front-loads the verb and core purpose without extraneous detail. It effectively communicates the tool's function.
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?
The tool is simple with optional parameters and an output schema. The description covers the returned fields but omits parameter semantics and usage context, making the description only partially 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?
The schema description coverage is 0%, and the description does not explain the 'limit' or 'query' parameters. While the schema provides types and defaults, the description adds no semantic meaning, leaving the agent to guess how filtering and pagination work.
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 'List' with the resource 'indexed documents' and enumerates the returned fields (stable IDs, titles, page counts, status). This clearly differentiates it from sibling tools like search or grep, which focus on content retrieval.
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 alternatives. The description simply lists what it does without mentioning any exclusions or preferred contexts, leaving the agent to infer usage.
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 full burden of behavioral disclosure. It discloses that the tool retrieves matching passages and produces unified diffs, which indicates a read-oriented operation, but it does not mention side effects, permission requirements, or how it handles missing documents or edge cases. The disclosure is useful but minimal.
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 compact sentence that conveys the core functionality with zero unnecessary words. It is well-structured and front-loaded, earning a perfect score for conciseness.
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 the tool has four parameters, no annotations, and no output schema, the description is too sparse. It lacks usage context, parameter explanations, output structure details, and how it differs from sibling tools. For an agent to invoke the tool correctly, significantly more context is needed.
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 description coverage is 0%, so the description should compensate by explaining parameters. It only alludes to 'two documents' without defining query, top_k, or how left_document_id and right_document_id map. The parameter names in the schema are somewhat self-explanatory, but the description adds little semantic value beyond what the schema already implies.
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 compares two documents by retrieving matching passages and returning aligned unified diffs. This specific verb+resource combination distinguishes it from siblings like search, grep, and read, which focus on searching or reading rather than multi-document comparison.
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 the tool is used for comparing two documents, but it does not explicitly state when to choose it over alternatives such as search or grep, nor does it provide exclusions or context about when not to use it. The intended use is clear but not strongly differentiated.
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?
No annotations are provided, so the description carries the burden of behavioral disclosure. It notes a constraint ('one to four PDF pages') and the output type ('images'), but does not mention side effects, permissions, or return format beyond what the schema implies.
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?
A single, front-loaded sentence communicates the key information without redundancy. It is concise and well-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?
With 4 parameters, no output schema, and no annotations, the description provides essential purpose and a page limit, but lacks detail on output structure and parameter semantics. It is adequate but not comprehensive for the tool's complexity.
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?
The schema description coverage is 0%, yet the description barely addresses parameters. It hints at the pages parameter via 'one to four', but does not explain document_id, dpi, or format, leaving the agent to rely on schema structure 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 uses a specific verb ('Render') and resource ('PDF pages as images'), stating a clear intended purpose 'for visual inspection'. This distinguishes it from sibling tools like read (text extraction) and compare (comparison).
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 implies when to use the tool ('for visual inspection'), providing clear context. However, it does not explicitly mention when not to use it or name alternative tools for other scenarios.
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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