knowflow

by Bipin-24

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.0.1
Disambiguation5/5
Each tool has a clearly distinct purpose: evaluating pipelines, checking build status, finding content gaps, retrieving topics, listing topics, and searching docs. No overlap in functionality.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern in snake_case (e.g., evaluate_pipeline, get_build_status, search_docs), making the set predictable and easy to navigate.
Tool Count5/5
With 6 tools, the server is well-scoped for its purpose of documentation knowledge management and pipeline evaluation. The count is neither too sparse nor overwhelming.
Completeness3/5
The server provides read and analysis capabilities (list, get, search, evaluate) but lacks tools for creating, updating, or deleting topics, which are notable gaps for a documentation system.
Average 3.3/5 across 6 of 6 tools scored. Lowest: 2.3/5.
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
- Last stable release on June 26, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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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 full burden for behavioral disclosure, but it only states it is a browse operation. No information about rate limits, authentication, return format, pagination, or potential side effects is given.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, which is too underspecified to be effective. It lacks structure and fails to convey necessary details efficiently.
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 lack of output schema, annotations, and meaningful parameter explanations, the description is incomplete. It does not clarify return values, behavior under different filters, or how to interpret results.
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?
Input schema has 0% description coverage and two parameters (product, topic_type) with enums. The description says 'optional filters' but does not explain what the filters mean or how they affect results, failing to compensate for the schema gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Browse the full corpus index with optional filters,' which suggests listing or exploring topics but lacks a specific verb-resource combination. It vaguely indicates the tool's purpose but does not distinguish it from siblings like get_topic or search_docs.
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 such as search_docs or get_topic. The description does not mention context, prerequisites, or exclusion conditions.
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, and the description does not disclose behavioral traits such as whether the tool is read-only, any side effects, or rate limits. For a tool that likely performs a read operation, this lack of transparency is a gap.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at one sentence, which is efficient for a simple tool. However, it lacks structural elements like bullet points or separate sections for usage notes, which could improve scannability.
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 has no output schema and only one parameter, the description is minimally complete. However, it slightly lacks context about what the status output contains (e.g., success/failure, build number). Additional details would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with a default value and description for the only parameter. The description adds no additional meaning beyond the schema, but the schema is self-sufficient. 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's purpose: checking the status of a Jenkins CI/CD publish pipeline. It uses a specific verb ('Check') and resource, distinguishing it from siblings like 'evaluate_pipeline' which likely analyzes pipeline performance rather than just status.
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?
There is no guidance on when to use this tool versus alternatives, nor any mention of prerequisites or context. The single sentence does not help an agent decide if 'get_build_status' is appropriate compared to 'evaluate_pipeline' or other tools.
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 must disclose behavioral traits. It only lists the metrics measured and mentions 'Run evaluation', but it does not indicate whether the tool is read-only, whether it modifies any state, what the output format looks like, or any side effects. This is insufficient for a tool with no annotation support.
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 short sentences with clear structure, front-loading the purpose. Every word adds value, and there is no redundancy or filler.
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 (two parameters, no output schema), the description covers the core purpose and metrics but omits details like expected output format, performance implications, or assumptions about the pipeline. It is minimally complete for an agent, but lacks behavioral context.
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 50% (only 'queries' parameter has a description). The description adds context by naming the metrics evaluated, suggesting how queries are used, but it does not provide additional meaning beyond the schema for 'report_format' (no description in schema or description). This is baseline adequate but not compensatory.
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 it runs RAGAS-style evaluation on the RAG pipeline and lists the specific metrics measured (answer relevance, faithfulness, context recall). This differentiates it well from sibling tools like get_build_status or search_docs.
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 for evaluating a RAG pipeline on test queries, but it does not explicitly state when to use it versus alternatives, nor does it mention prerequisites or when not to use it. The sibling tools provide context, but no exclusions are given.
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, and the description lacks details about behavioral traits such as idempotency, permissions, or whether it modifies data. The description only indicates a read-only operation implicitly.
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 effectively conveys the tool's purpose without unnecessary words or repetition.
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 absence of an output schema, the description could provide more context about the return format or example results. However, for a simple retrieval tool with default parameters, the description is adequate but not complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers all three parameters with descriptions, achieving 100% coverage. The tool description does not add additional semantic context beyond the schema, so a 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 clearly states the tool's purpose with a specific verb ('surface') and resource ('search queries that returned zero or low results'), and provides context about solving a documentation need. It is distinct from sibling tools like 'search_docs' or 'list_topics'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for finding content gaps but does not explicitly state when to use this tool versus alternatives, nor does it provide 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description must carry full burden. While it implies a read operation, it does not explicitly state read-only behavior, side effects, or other traits beyond the obvious retrieval.
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 unnecessary words. Concise and front-loaded with the action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple retrieval tool with one required parameter and no output schema, the description is sufficient. It covers what the tool does and what input is needed.
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% (topic_id described). The description adds no additional meaning beyond schema; baseline 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 clearly states the action ('Retrieve'), resource ('full Markdown content of a topic'), and method ('by ID'). It distinguishes from sibling tools like list_topics and search_docs.
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?
No explicit when-to-use or when-not-to-use guidance. The schema parameter description hints at a workflow (use with search_docs), but the tool description itself lacks usage context compared to alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full behavioral disclosure. It accurately states the tool performs a search and returns ranked results with scores and excerpts, indicating a read-only operation. It does not disclose potential edge cases like empty results or performance considerations, but the core behavior is clear.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the tool's core purpose and output. There is no unnecessary wording, and every part of the sentence adds value.
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 the tool has 4 parameters (all documented in schema) and no output schema, the description sufficiently explains the output format (ranked topics, relevance scores, excerpts). It could elaborate on ranking order or result limits, but the overall context is adequate for a search 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%, so parameters are already described in the input schema. The description does not add meaningful context beyond the schema, such as how parameters interact or recommended usage patterns. The phrase 'semantic search' only reinforces the schema's natural language 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 it performs 'semantic search across the documentation corpus' and returns 'ranked topics with relevance scores and excerpts.' It uses specific verbs and resources, and distinguishes from siblings like 'get_topic' and 'list_topics' by specifying search and ranking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for finding documentation topics via natural language, but does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternative tools like 'get_topic' for single topic retrieval.
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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