knowledge-rag

by lyonzin

Overview Schema Related Servers Score Discussions

Python

Local

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v4.8.5
Disambiguation5/5
Each tool has a clearly distinct purpose. add_document and add_from_url differ by input source; search_knowledge and search_similar differ by query type; all other tools are uniquely defined with no overlap.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, e.g., add_document, list_documents, search_knowledge. The one minor variation 'add_from_url' still starts with a verb and is clear.
Tool Count5/5
12 tools is well-scoped for a knowledge base server. Each tool corresponds to a distinct operation (CRUD, search, listing, evaluation, reindex), and none seem extraneous.
Completeness5/5
The tool surface covers all typical operations: document creation (text/URL), retrieval, update, delete, listing, category browsing, search (hybrid and similarity), search evaluation, reindexing, and health stats. No obvious gaps.
Average 4.9/5 across 12 of 12 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 34 of 34 community issues answered or closed in the last 6 months
- 120 commits in the last 12 weeks
- Last stable release on August 14, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
This repository includes a glama.json configuration file.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?
States 'Read-only. No side effects' which is important for behavior. Discloses return format and parameter constraints. Lacks info on error handling or rate limits, but sufficient for this simple tool.
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?
Well-structured with summary, behavior, params, returns, and usage. Front-loaded with purpose. Slightly verbose but each sentence adds value.
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?
Covers all needed aspects: purpose, parameters, return format, usage context, and alternatives. Output schema exists, so return details are sufficient. Annotations missing but description fills gaps.
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?
The only parameter 'category' has no schema description (0% coverage). The description compensates fully by explaining it's optional, must be a valid category name, and suggests calling list_categories for options, with examples.
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 (list) and resource (indexed documents) with an optional category filter. It distinguishes from siblings by mentioning when to use alternatives like search_knowledge and get_document.
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?
Explicit guidance on when to use this tool (browsing index, verifying file) and when not (use list_categories first, use search_knowledge for topics, use get_document for reading). Includes specific alternative 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?
No annotations provided, so description carries full burden. It says 'Read-only. Runs multiple search queries internally. No side effects on the index.' It also explains the return value structure (MRR@5, Recall@5, etc.) and expected threshold. However, it does not mention potential performance impact or rate limiting, but for a quality evaluation tool, this is reasonably transparent.
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 well-structured: first sentence states purpose, then line about side effects, then parameter explanation with example, then return value description, then usage with alternatives. It is front-loaded with key info and not overly verbose.
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 the tool has only one parameter and an output schema exists (context says 'Has output schema: true'), the description is complete. It explains parameter format, return metrics, and usage context. No gaps.
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 0% because input schema only has 'test_cases' as a string with no description inside. The description provides a detailed explanation: 'JSON string array of test cases. Each item requires "query" (search string) and "expected_filepath"...' with an example. This fully compensates for the lack of schema description.
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: 'Evaluate search quality by testing whether search_knowledge() retrieves expected documents.' It specifies the verb 'evaluate' and the resource 'search quality/retrieval'. It distinguishes from siblings like 'search_knowledge' and 'get_index_stats' by mentioning them in the usage section.
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?
Explicitly states when to use: 'to audit search quality after bulk document ingestion or after tuning hybrid_alpha.' It also provides alternatives: 'Use get_index_stats() for system health checks instead. Use search_knowledge() for actual document retrieval — this tool is for quality measurement only.' This is excellent guidance.
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?
Declares 'Read-only. No side effects.' and describes return value format. With no annotations, the description carries full burden; it could mention error behavior for missing files, but overall adequate.
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?
Well-structured: purpose, behavior, args, returns, usage. Each sentence adds value without 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 the simple tool and presence of output schema, the description covers all needed aspects: usage, parameter, return value, and context.
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?
The schema has no description for filepath (0% coverage), but the description adds significant meaning: example path, relative path constraint, and pointers to find valid paths.
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: 'Get the full content of a specific document by filepath.' It distinguishes from siblings by noting that search_knowledge returns chunks and list_documents browses files.
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?
Explicitly says when to use ('when you need the complete text of a known file') and provides clear guidance on alternatives (search_knowledge first if unknown, list_documents to browse).
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?
The description discloses all behavioral aspects: mutating, outbound HTTP, internet access required, HTML stripping, markdown conversion, disk save, immediate indexing. This is thorough and compensates for the lack of annotations.
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 well-structured with intro, behavior, Args, Returns, and Usage sections. It is slightly verbose but efficiently conveys all necessary information.
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?
The description is complete: covers behavior, parameters, return value (JSON string with details), and usage context. It also mentions immediate searchability, leaving no ambiguity.
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?
With 0% schema description coverage, the description fully explains each parameter: url requires HTTPS and public accessibility, category lists possible values, title is optional and auto-detected. This adds significant meaning 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 the tool fetches content from a URL, converts to markdown, and adds to the knowledge base. It distinguishes itself from the sibling tool add_document by specifying when to use each.
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?
Explicit usage guidance is provided: 'Use to ingest web content... Use add_document() instead when you already have text content.' This clearly tells when and when not to use the tool.
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?
Declares read-only and no side effects. Lists return fields in detail: total documents, chunks, embedding model name, BM25 status, cache hit rate, file watcher status. With no annotations provided, the description fully carries the burden of 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?
Very concise and well-structured. Opens with purpose, then read-only note, then lists return values, then usage guidance with alternatives. Every sentence is informative with no fluff.
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 zero parameters and an output schema, the description explains what the tool returns and its safe, read-only nature. It is completely adequate for an AI agent to understand 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?
No parameters exist, so schema coverage is 100%. The description adds no parameter info because none are needed. Baseline of 4 is appropriate for zero parameters.
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 gets statistics and health metrics for the knowledge base index. It uses specific verb+resource and distinguishes from sibling tools like list_categories and evaluate_retrieval.
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?
Provides explicit usage scenarios: system health checks, verifying embedding model, checking index population, monitoring cache efficiency. Also tells when not to use by naming alternatives (list_categories for per-category counts, evaluate_retrieval for search quality).
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 no annotations, the description discloses that the tool is lightweight and does not compute full index statistics. It details the return structure for both active and inactive states, providing full behavioral 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 concise and well-structured. The first sentence gives the core purpose, followed by important details in a logical order. Returns are listed compactly, and usage instructions are clear. No unnecessary 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?
Given no parameters and an output schema, the description thoroughly explains the return value and usage context. It also references sibling tools for completeness. The tool is simple, and the description covers all needed information.
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 no parameters, so the input schema fully covers parameter semantics. The description adds value by explaining the return format, which is beyond what the schema provides. Baseline 4 for no parameters 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 clearly states the tool gets the current status of a background reindex operation. It uses a specific verb ('Get') and resource ('reindex status'), and distinguishes from sibling tools like 'get_index_stats' and 'reindex_documents'.
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 explicitly says when to use: poll after calling reindex_documents. It also provides an alternative: use get_index_stats for full index health. This gives clear guidance on tool selection.
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?
The description states the tool is read-only with no side effects and reflects the live index state. Since no annotations are provided, this fully covers behavioral traits such as safety and data freshness.
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 three short sentences, each adding value: purpose, behavior, and usage guidance. It is efficiently front-loaded with the core purpose.
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 the tool is parameterless and has an output schema, the description covers everything needed: what it does, what it returns (category names, counts, total), and when to use it. No gaps.
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 input schema has zero parameters and schema description coverage is 100% (trivially). There are no parameters to explain, so the description adds no parameter semantics, but this is acceptable for a parameterless tool. Baseline 4 for 0 params.
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 document categories with their document counts, using a specific verb ('List') and resource ('document categories'). It is distinct from siblings like 'list_documents' which lists documents, not categories.
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 explicitly advises using this tool before filtering search_knowledge or list_documents by category, and suggests get_index_stats as an alternative for broader system health metrics. This provides clear when-to-use and 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.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, description fully discloses behavior: 'Mutating — overwrites the file on disk and re-indexes immediately. Old chunks are removed and replaced with new ones. Full content replacement, not a patch.' Also states changes are immediately searchable.
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?
Well-structured with separate sections for behavior, args, returns, and usage. Every sentence is informative, though slightly verbose. Front-loaded with purpose and behavior.
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 mutation tool with reindexing and full replacement, description covers prerequisites, effects, and output. References sibling tools for alternative actions. No gaps given the complexity.
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 0%, but description explains both parameters: filepath must be an already-indexed file and reference to list_documents(), content is full-text replacement. Also describes return value format.
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?
Clearly states 'Update the content of an existing document' with specific verb and resource. Distinguishes from siblings add_document and remove_document directly in the usage section.
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?
Explicitly tells when to use (replace content completely), when not (use add_document for new files, remove_document for deletion), and prerequisite (file must already be indexed, use list_documents to find paths).
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?
With no annotations, the description fully discloses behavioral traits: mutating, writes to disk, indexes immediately, no auth, and returns JSON with specified fields.
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?
Concise and well-structured: purpose statement, behavioral note, parameter descriptions, return value, and usage guidelines. Every sentence adds value without verbosity.
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 no annotations and 0% schema descriptions, the description covers all necessary aspects: purpose, parameters, behavior, return format, and usage context with sibling differentiation.
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 description coverage is 0%, but the description adds detailed semantics for all three parameters: markdown support for content, path conventions for filepath, and category enumeration with default.
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 adds a document from raw text content, distinguishes from siblings like add_from_url and update_document, and mentions immediate searchability, making purpose very clear.
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?
Explicitly provides when to use this tool (text content) and when to use alternatives (add_from_url for web pages, update_document for replacing files), plus notes no auth required.
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?
With no annotations, the description fully bears the transparency burden. It discloses background execution, status polling via get_reindex_status(), silent fallback on checkpoint issues, and destructive deletion in full_rebuild ("nuclear rebuild (delete + re-embed)"). This goes well beyond basic expectations.
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 efficiently structured: the purpose is front-loaded, each parameter is explained on its own line, and the closing note ties everything together. Every sentence provides necessary context—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?
The description is complete for a tool with three nuanced flags: it covers purpose, usage scenarios, background behavior, status polling, and the relationship to sibling tools. The output schema exists, but the description additionally clarifies the polling mechanism, making it self-sufficient.
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?
The input schema has no descriptions (0% coverage), but the description fully explains each parameter: force as smart reindex, full_rebuild as destructive rebuild with mutual exclusivity with resume, and resume with checkpoint path and fallback behavior. This adds essential meaning beyond the bare 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 "Index or reindex all documents in the knowledge base (runs in background)", which clearly states the verb, resource, and scope. It distinguishes itself from siblings by explicitly noting that add/update/URL tools already auto-index, so this tool is for recovery/rebuild scenarios.
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?
Explicit usage guidelines are provided for each flag: "Use after filesystem edits outside add_document/update_document" for force, "Use only after embedding-model change or index corruption" for full_rebuild, and a closing note that add/update/URL tools auto-index, so these flags are only for recovery/rebuild. This clearly states when to use the tool versus alternatives.
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?
Discloses mutating nature, removal of index entries, and irreversible deletion with delete_file=True. Since no annotations exist, description fully covers behavioral traits.
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?
Well-structured with summary, args, returns, usage. Every sentence adds value; no redundancy. Front-loaded with core action.
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 2 parameters, no annotations, but with output schema referenced, description thoroughly covers behavior, return format, and alternatives. No gaps.
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?
Adds crucial meaning beyond schema: filepath must be an indexed document and hints to use list_documents(); delete_file explains permanence and default. With 0% schema coverage, description compensates fully.
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 verb 'Remove' and the resource 'document from the knowledge base index'. It distinguishes from siblings like update_document and reindex_documents, providing specific context.
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?
Explicitly guides when to use (unindex a document) and when to set delete_file=True. Provides alternatives: update_document for replacement, reindex_documents for manual deletions.
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?
With no annotations provided, the description carries full burden and does so thoroughly. It discloses read-only nature ('Read-only. No side effects.'), snippet truncation behavior, min_score filtering, search_method dispatch behavior including compatibility notes, and return format.
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?
While long, the description is well-structured with sections (overview, read-only, Args, Returns, Usage) and each sentence earns its place. It is front-loaded with the primary purpose, and the parameter details are necessary for correct invocation.
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?
The description covers the return format (JSON string with content chunks, source filepath, relevance score, search method), parameter semantics, alternatives, and edge cases like FTS5 fast-path errors. Given the tool has 7 parameters and an output schema, this description is complete without relying on external documentation.
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 description coverage is 0%, so the description must compensate, and it excels. Every parameter is explained with practical guidance: query recommendations (1-3 keywords), hybrid_alpha semantics (keyword vs semantic), min_score tuning (0.2-0.4 to cut noise), and search_method behavior including a kill switch and debug use case.
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 'Hybrid search combining semantic search + BM25 keyword search with cross-encoder reranking,' clearly stating the tool's specific action (search) and resource (knowledge). It also differentiates from siblings by noting it 'Returns chunks, not full document content' and referencing search_similar and get_document.
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 Usage section explicitly states this is the 'Primary search tool' and names direct alternatives: 'Prefer search_similar() when you already have a reference document...' and 'Prefer get_document() when you already know the exact filepath...' This provides explicit when-to-use vs 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.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description fully carries the burden. It states 'Read-only. No side effects.' and explains the use of embeddings for similarity. Return format is described in detail.
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?
Description is concise and well-structured: brief summary, behavioral note, args list, returns, usage. Every sentence adds value without 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 the tool's simplicity and presence of output schema, description covers all needed aspects: purpose, usage, parameters, behavior, and return format. No gaps identified.
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 0%, so description compensates by fully explaining both parameters: filepath (path, must be indexed, example) and max_results (default and max). This adds significant meaning beyond the bare schema types.
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 action: 'Find documents semantically similar to a given reference document.' It distinguishes from sibling tool 'search_knowledge' by specifying it works with a reference document, not a text query.
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?
Explicitly states when to use: when you have a specific document, and when not: use search_knowledge for text queries. Also includes prerequisite that document must be indexed and suggests verifying with list_documents().
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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