RepoChatMCP

by gzmagyari

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.11
Disambiguation4/5
Tools are mostly distinct, clearly separated into session management, chat search, and knowledge indexing. Some overlap exists between chat.search (relevance scoring) and chat.grep (regex), and among the various knowledge reading tools, but descriptions clarify their different purposes.
Naming Consistency4/5
All tools use snake_case and the chat. prefix, generally following a verb_noun pattern (list_sessions, read_session, start_knowledge_index). There is one deviation ('compaction_knowledge' is noun-like) and a mix of verbs like search/grep/read, but overall the naming is consistent and readable.
Tool Count5/5
15 tools is within the ideal 3-15 range for a focused MCP server. Each tool addresses a specific aspect of chat session access or knowledge indexing, and none feel redundant or unnecessary.
Completeness4/5
The tool set covers the core lifecycle of knowledge indexing (start, cancel, status, read artifacts) and session discovery/reading. Minor gaps include no ability to list all indexes at a high level (only batches) and no explicit session deletion, but these are not critical for the server's apparent purpose.
Average 3.3/5 across 15 of 15 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 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.
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.
Add a glama.json file to provide metadata about your server.
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

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 behavioral disclosure. It only says 'Read messages' but does not explain message ordering, pagination behavior, default limits, error handling, or implications of the 'limit' and 'startIndex' parameters. It's a minimal read operation but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no fluff, but it is under-specified. It states the core purpose but does not earn its place by adding value beyond the tool name; however, since the title is null, it serves as the only textual anchor. It is concise but could be more informative without becoming verbose.
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 6 parameters, no output schema, and no annotations, the description is incomplete. It fails to explain the meaning of message types, index ranges, or provider hints, and does not describe the return format. The user would need to rely heavily on parameter names and examples.
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 does not add any extra semantics beyond what the schema already provides, which is acceptable given the high coverage.
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 action (read) and the resource (messages from a specific session). It is specific enough to distinguish from generic tools, though it doesn't explicitly differentiate it from similar sibling tools like chat.read_lines or chat.search.
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 vs alternatives such as chat.list_sessions, chat.search, or chat.read_lines. There is no mention of context, prerequisites, or exclusions.
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 exist, so the description carries full responsibility for behavioral disclosure. It mentions returning a file path, which hints at possible snapshot creation, but does not state side effects, permissions, whether the operation is read-only, or the lifecycle of the returned path. The description adds only minimal context beyond the tool 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 sentence that front-loads the action and outcome. It is appropriately brief, though it could be slightly clearer about the nature of 'compaction knowledge metadata' without becoming verbose.
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?
With no output schema and a non-trivial purpose, the description leaves significant gaps: what a compaction snapshot is, how the returned path should be used, and how this tool relates to siblings like read_latest_knowledge or start_knowledge_index. The description provides only a high-level summary that is insufficient for confident invocation.
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 parameter descriptions already document each parameter meaning. The tool description does not add any parameter-level detail beyond what the schema provides, making the baseline score of 3 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 uses a specific verb ('Collect') and identifies a concrete resource ('live compaction knowledge metadata'), and clearly states the outcome ('return an absolute file path for the compaction snapshot'). This distinguishes it from sibling tools focused on general knowledge search or sessions, though the term 'compaction knowledge' is not fully explained.
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 the many sibling knowledge tools. No context is provided about whether this is a read-only operation, whether it should be used before/after other compaction tools, or what conditions favor selecting it.
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 provided, the description carries the full burden of behavioral disclosure. It mentions pattern syntax but omits important behavioral details such as result ordering, pagination, default session scope, or how context messages are handled. This is insufficient for an unannotated 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?
The description is a single, efficient sentence that front-loads the core purpose and key features. It contains no wasted words, though it omits important context that would make it more complete.
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 7 parameters, no output schema, and no annotations, the description is too sparse. It fails to explain return value structure, how sessions are scoped, or how limits and context parameters affect results. This is a significant gap for a tool of this complexity.
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 schema already documents all 7 parameters with descriptions, so baseline is 3. The tool description's note about pattern syntax is redundant with the pattern parameter description, adding no extra semantic value beyond what the schema provides.
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 function: grep chat messages by pattern, with explicit support for |, &, and regex. This is a specific verb+resource combination that distinguishes it from generic search, though it does not explicitly differentiate from the sibling chat.search tool.
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 like chat.search. There is no mention of exclusions, prerequisites, or typical scenarios where grep is preferred over other search methods.
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 provided, the description carries the full burden of behavioral disclosure. It only mentions 'persisted' and 'canonical combined artifact information,' but does not explain pagination, default limits, filtering semantics, or what distinguishes a 'persisted' batch from non-persisted ones.
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 sentence, front-loaded with the action and resource. The phrase 'canonical combined artifact information' is somewhat unclear, but there is no fluff or redundant text.
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?
Without an output schema, the description should explain what the returned list contains and how to use the parameters. It barely hints at the output ('combined artifact information') and omits behavioral details like limit defaults and filtering, making it incomplete given the complexity of the sibling tools (e.g., start/cancel index, status).
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 already covers both parameters (limit and provider) with clear descriptions, so 100% schema coverage is achieved. The description adds no additional meaning to the parameters, so the 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 identifies the action ('List') and resource ('persisted knowledge batches'), which distinguishes it from sibling tools like 'read_knowledge_batch' (single-read) and 'list_knowledge_files' (files, not batches). However, 'canonical combined artifact information' is vague and doesn't fully clarify what the listed batches contain.
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 such as 'read_knowledge_batch' or 'list_knowledge_files'. It states what it does but does not specify when it is the right choice or what it should be used for within the broader knowledge-index workflow.
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 provided, the description must disclose behavioral traits itself. It only mentions 'relevance scoring', but does not state that the operation is read-only, the return format, or any side effects. It also omits details about pagination or how results are ordered.
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, focused sentence with no unnecessary words. It front-loads the action and directly states the purpose, making it highly efficient.
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 absence of an output schema and annotations, the description should provide more context about return values and operational behavior. It is overly minimal, leaving important aspects like result format and context window behavior unspecified.
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% description coverage for all six parameters, so the baseline is 3. The description adds no extra meaning about parameters beyond the schema; it only repeats the query concept.
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 searches chat messages using a text query and relevance scoring. It is specific about the verb and resource, but does not explicitly contrast with sibling tools like chat.grep or chat.search_knowledge.
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. It does not mention any exclusion criteria or reference other sibling tools, leaving the agent without context for tool selection.
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, the description carries full responsibility for behavioral disclosure. It only mentions 'discovered' sessions, which is vague, and provides no details on whether the operation is read-only, how archival filtering works by default, or what the returned sessions look like.
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 entire description is a single concise sentence that front-loads the verb and resource. Every word earns its place; there is no redundancy or unnecessary detail.
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 two well-documented parameters, but the description lacks an output schema and does not clarify what 'sessions' are or what 'discovered' means. It is minimally adequate for a list operation, but would benefit from mentioning return format or typical usage.
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 schema descriptions cover both parameters fully (provider and includeArchived), so the baseline is 3. The description adds no additional meaning about these fields, leaving the schema as the sole source of parameter semantics.
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 action ('List') and the resource ('discovered chat sessions for the current repo'), making the tool's purpose obvious. It doesn't explicitly differentiate from siblings, but the resource scope is unique enough to avoid confusion.
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 like chat.search or chat.read_session. The description gives no exclusions, prerequisites, or context on how this list should be used in a workflow.
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, the description must fully disclose behavior. It only says 'search' and 'return snippet matches,' which implies a read-only operation but does not explicitly confirm safety, state prerequisites (e.g., whether knowledge must be indexed first), or explain what 'directly' means. This leaves significant behavioral ambiguity for an agent.
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, focused sentence with no redundant words. It states the action and expected output in a clear, front-loaded structure, earning every word.
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?
The description is too sparse given the lack of annotations, the presence of 4 parameters, and a complex sibling set. It omits practical context like whether prior indexing is required, how results are scoped, or when to prefer this over chat.search or chat.grep. The phrase 'persisted knowledge artifacts' hints at scope but does not elaborate.
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 schema provides 100% parameter descriptions, so the baseline is 3. The description does not add additional meaning about parameter usage beyond the schema, such as how 'kind', 'limit', or 'batchId' influence the search. It simply states the overall purpose.
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 ('Search') and resource ('persisted knowledge artifacts'), clearly stating the action and target. The phrase 'directly' and 'snippet matches' adds specificity, and the naming distinguishes it from siblings like chat.search and chat.grep.
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 provided about when to use this tool versus alternatives. It does not mention exclusions, prerequisites, or competing sibling tools. The implied use case is search, but there is no direct comparison to chat.search or chat.grep.
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, the description carries full burden for behavioral disclosure. It only states 'paginated text' and 'persisted', but fails to mention default limits, offset semantics, error behavior, or return format beyond plain text. This adds marginal value beyond the tool name.
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 that gets straight to the point with no extraneous information. Every word is useful.
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 description is adequate for a read operation with a well-documented schema, but without an output schema or annotations it leaves gaps about return structure and usage context. It is missing when-to-use guidance relative to sibling tools.
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%, with each parameter (kind, limit, offset, batchId) already described. The description itself adds no additional parameter context or examples, so it stays at the baseline.
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 ('read') and resource ('persisted knowledge batch artifact'), and 'paginated text' clarifies the output format. It clearly distinguishes from sibling tools like list_knowledge_batches or read_latest_knowledge.
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 read_knowledge_file, read_latest_knowledge, or search_knowledge, and only implies usage through the schema-required batchId parameter.
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 conveys pagination, read-only nature ('Read'), and file specificity, but does not mention error handling, required permissions, or behavior on invalid runId.
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 concise sentence that front-loads the action ('Read') and resource. No wasted words, clearly structured for quick scanning.
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 has only 3 simple parameters and no output schema. The description explains it reads paginated text, which is adequate for basic invocation, but lacks details on return format or edge cases and doesn't differentiate from sibling tools.
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 all parameters (runId, limit, offset) described in the schema. The description adds context about pagination that maps to limit/offset, but no new semantics beyond the schema. Baseline of 3 applies.
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 'Read paginated text from a specific persisted per-chunk knowledge file' with a specific verb and resource. It distinguishes this from sibling tools like read_knowledge_batch by emphasizing 'specific' and 'per-chunk', though it doesn't explicitly name alternatives.
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 this tool versus siblings like read_latest_knowledge or search_knowledge. The description implies use for reading a known file with pagination, but lacks exclusions or alternative recommendations.
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 disclosing safety and behavior. It does state that this is a read operation and that it returns paginated text, which gives basic transparency. Missing details include error handling, output format specifics, and what 'combined' means.
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, front-loaded sentence that clearly conveys the core action and object. No wasted words.
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 a straightforward read operation, but without annotations or an output schema, and with many sibling tools, the description leaves the concept of 'combined knowledge artifact' underdefined. It does not explain how it differs from reading a batch or file. This is functional 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?
Schema coverage is 100%, so the schema already fully describes all parameters. The description adds no extra parameter meaning beyond hinting at the artifact type, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Read') and resource ('latest persisted combined knowledge artifact'), which distinguishes it from siblings like read_knowledge_batch or read_knowledge_file. However, the term 'combined knowledge artifact' is not defined, leaving some ambiguity.
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 gives no explicit guidance on when to use this tool versus alternatives. It only implies usage through the word 'latest', but does not clarify scenarios or mention 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 carries the transparency burden. The verb 'Read' implies a read-only operation, and the description conveys the selection modes. However, it does not disclose interactions between parameters (e.g., using start/end with aroundKeyword/aroundRegex), edge cases, or any potential modifications, leaving behavioral gaps.
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, front-loaded sentence with no filler, redundancy, or irrelevant details. It states the core function clearly and efficiently, every word earning its place.
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 seven parameters, no annotations, and no output schema, the description is adequate but not complete. It explains the primary purpose but lacks usage context (when to prefer this over siblings), how optional parameters interact, and what the return value looks like, leaving room for ambiguity in real-world use.
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 schema already documents all seven parameters, including types and descriptions. The description adds no additional meaning beyond high-level grouping of keyword/regex to lines, so it does not improve on the schema, warranting the baseline score of 3.
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 uses the specific verb 'Read' and identifies the resource as 'lines from a session', with two clear modes: specific lines or lines around a keyword/regex. This is distinct from reading an entire session, though it does not explicitly name sibling tools like chat.read_session or chat.grep to differentiate.
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 given on when to use this tool versus alternatives such as chat.read_session, chat.grep, or chat.search. The description only states the function, with no mention of preferred contexts, exclusions, or competing 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?
The description notes that the operation is a 'request' and that the job is 'async', giving some behavioral context. However, it does not disclose the return value, failure modes, idempotency, or permissions needed. With no annotations, the description carries the full burden and should offer more 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, well-structured sentence that front-loads the action and includes no redundant words. It is appropriately sized for the tool's simplicity.
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?
For a one-parameter tool with no output schema, the description is adequate but lacks guidance on what to do after canceling (e.g., checking status) or what the expected response is. It does not explain edge cases, which would improve completeness.
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 already describes jobId as 'Knowledge indexing job ID' with 100% coverage. The description adds no extra parameter semantics, so the baseline score of 3 applies.
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 (request cancellation) and the target (async repository knowledge indexing job). It distinguishes this from sibling tools like start_knowledge_index and get_knowledge_index_status by naming the specific operation.
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 when you want to cancel an indexing job, but it provides no explicit when-to-use or when-not-to-use guidance, nor any preconditions or alternatives. Context from sibling names helps but is not stated.
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. The word 'List' signals a read-only operation and 'persisted per-chunk' adds context, but it does not disclose response format, pagination, or error behavior.
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, front-loaded with the verb, and contains no filler or redundant words.
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 list tool with two fully described parameters and no output schema, the description adequately conveys purpose and result. It does not explain return shape or edge cases, but low complexity and sibling context make it reasonably 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?
Schema description coverage is 100%, with batchId described as 'Knowledge batch ID' and kind as 'knowledge or content_summary'. The tool description adds no parameter-level meaning beyond this complete schema coverage, so baseline 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 uses the specific verb 'List' with a clear resource ('persisted per-chunk knowledge files') and scope ('for a specific batch'), distinguishing it from sibling tools that list batches or read individual files.
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 phrase 'for a specific batch' implies the tool is used when you have a batch ID and want its files, but it does not explicitly state when to prefer it over alternatives like read_knowledge_file, nor does it provide exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It notes the job is 'async', which is useful context, but it doesn't explain what 'status and progress' means exactly (e.g., possible states, error behavior, or whether the operation is read-only). For a simple status getter, this is adequate but not rich.
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, front-loaded sentence that immediately conveys the tool's purpose. No wasted words or repetitive information. It is appropriately concise and well-structured.
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 one-parameter status-checking tool, the description is mostly complete. It doesn't describe the return format or possible statuses, but given no output schema, the agent can infer it returns progress details. It could be richer, but it's adequate for this low-complexity 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 description coverage is 100%: the 'jobId' parameter is described as 'Knowledge indexing job ID'. The tool description adds no additional parameter semantics beyond what the schema already provides. Baseline of 3 is appropriate since the schema handles parameter explanation.
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 function with a specific verb ('Get') and resource ('status and progress of an async repository knowledge indexing job'). It distinguishes itself from sibling tools like start_knowledge_index, cancel_knowledge_index, and list_knowledge_batches by focusing on status retrieval.
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 provides clear context for when to use this tool: after initiating an async indexing job, you'd call this to check its status. It doesn't explicitly mention alternatives or exclusions, but the purpose is obvious given sibling tool names. This is clear context without exclusions, matching a score of 4.
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 the burden and adequately discloses the key behavior: it's an async job that returns immediately with a job ID. It doesn't describe side effects like rebuilding or persistence, but the schema covers the force parameter, and the core async trait is clearly stated.
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 is front-loaded with the action and outcome, containing zero waste. It is concise and immediately informative.
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?
The tool is simple with two optional parameters and no output schema. The description mentions the return behavior (job ID), which is crucial. It lacks mention of related lifecycle tools, but this is not essential for the start operation.
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 both parameters fully described in the input schema. The tool description adds no further parameter nuance, 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 explicitly states the action ('Start'), the resource ('repository knowledge indexing'), and the async behavior with immediate job ID return. This clearly distinguishes it from sibling tools like cancel_knowledge_index or get_knowledge_index_status.
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 when to use this tool (to start indexing) but does not provide explicit guidance on alternatives or exclusions. It doesn't mention when not to use it or reference the related status/cancel tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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