SocratiCode

Server Quality Checklist

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

Latest release: v1.12.0
Disambiguation5/5
Each tool targets a distinct operation or query on the codebase: codebase_search vs codebase_context_search distinguish code vs context; codebase_symbol vs codebase_symbols separate single-symbol details from listing; codebase_flow vs codebase_impact differentiate call trees from blast radius. No two tools have overlapping purposes.
Naming Consistency5/5
All tools follow the 'codebase_verb_noun' pattern in snake_case (e.g., codebase_context_search, codebase_graph_build). No mixing of conventions or irregular names.
Tool Count4/5
25 tools is on the higher side but justified by the broad scope: indexing, search, graph analysis, context artifacts, symbols, flow, impact, watch, health, etc. Each tool serves a clear purpose, though some could be merged (e.g., graph build/status/remove).
Completeness5/5
The tool surface covers the full lifecycle of codebase analysis: index management, semantic search, dependency graph traversal, symbol introspection, impact analysis, context artifact handling, and project listing. No obvious gaps for the stated purpose of understanding and navigating codebases.
Average 4.1/5 across 25 of 25 tools scored. Lowest: 3.1/5.
See the Tool Scores section below for per-tool breakdowns.
- 45 of 45 community issues answered or closed in the last 6 months
- 96 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 passing
This repository is licensed under AGPL 3.0.
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

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 states the tool finds circular dependencies, without clarifying whether it is read-only, what side effects exist, or any other 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it 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?
The description lacks details about output format, return values, or whether results are a list of cycles, a graph, etc. Since no output schema exists, this omission leaves the agent underinformed.
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% for the single parameter (projectPath), so the description adds no extra meaning beyond the schema's definition. 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 'Find circular dependencies in the codebase' uses a specific verb ('find') and resource ('circular dependencies'), clearly stating the tool's purpose and distinguishing it from other graph-related tools like build, query, or stats.
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 codebase_graph_query or codebase_graph_visualize, leaving the agent without context for 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 bears full responsibility for transparency. It states the tool is a query (implying read-only) and returns data, but it does not disclose prerequisites (e.g., graph must be built), potential side effects, or error conditions. The read-only nature is implied but not explicit.
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 extremely concise: two sentences, no redundant words. The first sentence states the primary action, and the second clarifies the output. Ideal for quick parsing by an AI agent.
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 an output schema, the description should provide more detail about the return format (e.g., list of imports and dependents, structure). It does not mention error handling or edge cases (e.g., file not found, graph not built). For a query tool, this is a notable gap.
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 provides descriptions for both parameters (filePath and projectPath) with 100% coverage. The description adds no additional semantic information beyond what is in 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 action ('Query the code dependency graph') and specifically what it returns (imports and dependents for a given file). This distinguishes it from sibling tools like codebase_graph_build or codebase_graph_circular which handle other aspects of the dependency graph.
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. For example, it doesn't mention that the graph must be built first (via codebase_graph_build) or that this is for a single file query only. The user/AI must infer usage from the description alone.
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?
Since no annotations are present, the description carries the full burden. It discloses key behaviors: auto-indexes on first use and auto-detects stale artifacts. However, it does not mention side effects, auth requirements, rate limits, or error-handling behavior, leaving some transparency 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 extremely concise: two sentences with no wasted words. It is front-loaded with the core purpose ('Semantic search across context artifacts') and immediately provides key behavioral notes. Every sentence earns 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 there is no output schema and 5 parameters, the description adequately covers the main use case and indexing behavior. However, it lacks details about return format, RRF score interpretation, and the importance of 'projectPath'. This is adequate but not thorough.
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, so the baseline is 3. The description adds no extra meaning to the parameters; it only states 'semantic search' but does not elaborate on how parameters like 'minScore' or 'artifactName' interact. The schema descriptions are sufficient on their own.
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 performs semantic search across context artifacts (database schemas, API specs, etc.). It specifies the resource and action, making the purpose easy to understand. However, it does not explicitly differentiate from sibling tools like 'codebase_search' or 'codebase_context', so it falls short of a 5.
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 a usage hint ('Use this to find relevant infrastructure or domain knowledge') but does not give any guidance on when to use this tool versus alternatives like 'codebase_search' or 'codebase_context'. There is no mention of when not to use it or explicit comparisons.
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 carries full burden. It fails to disclose prerequisites (e.g., graph must be built via codebase_graph_build), side effects, or performance implications. Only the output is described, leaving critical behavioral context missing.
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-front-loaded sentence that efficiently conveys the tool's function and outputs without extraneous 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?
Given the tool's simplicity (1 param, no output schema), the description adequately lists the statistics returned but omits important context such as the need for a pre-built dependency graph, which impacts 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?
Schema coverage for the single parameter (projectPath) is 100%, with a clear description in the schema. The description adds no further parameter information, meeting the baseline for high schema coverage.
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 specifies 'Get statistics about the code dependency graph' and enumerates the outputs (total files, edges, most connected files, orphan files, circular dependencies), effectively distinguishing it from sibling tools like codebase_graph_build and codebase_graph_circular.
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 retrieving overall graph statistics but provides no explicit guidance on when to use this tool vs alternatives like codebase_graph_query or codebase_graph_circular. No when-not-to-use or prerequisite mentions.
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, description covers initial incremental update and debounced watching. However, it does not disclose potential resource consumption, limitations, or side effects of stopping. 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?
Two sentences, no redundancy. All information is essential and front-loaded. Efficiently conveys core behavior.
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?
No output schema, but description does not explain return values for 'status' action or confirm behavior on stop. Given complexity, it could be more complete about operational details.
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% (both parameters described). The description does not add new meaning beyond the schema's property descriptions, 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?
Clear verb 'Start/stop watching' and resource 'project directory for file changes and automatically update the index'. The description differentiates from siblings like codebase_update by specifying continuous watching behavior.
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?
Implies usage for continuous indexing but lacks explicit guidance on when to use this tool versus alternatives like codebase_update (manual update) or codebase_status (snapshot). No when-not-to-use or context for stopping.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden. It discloses that only indexed projects are listed, but lacks details on pagination, ordering, or whether it returns all projects or a subset.
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, clear sentence with no redundant information. It is front-loaded with the action and resource.
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 tool with no parameters and no output schema, the description adequately covers the purpose and scope. It could mention output format or ordering, but it is sufficient for a simple list operation.
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?
Since there are no parameters, the description adds value by clarifying that only indexed projects (those with Qdrant collections) are included. This goes beyond the empty 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 action ('List') and the resource ('projects that have been indexed'), with a precise condition ('have collections in Qdrant'). This distinguishes it from sibling tools that deal with context, search, or other project operations.
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. There is no mention of when not to use it or any related tools for filtering or searching projects.
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?
Without annotations, the description alone must disclose behavioral traits. It reveals that the tool is blocked during indexing, which is useful. However, it omits other traits such as whether removal is reversible, what happens if no artifacts exist, or any authentication requirements.
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 consists of two succinct sentences: the first states the purpose, and the second provides a critical behavioral warning. Both are essential and efficiently presented with no unnecessary 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?
Given the tool's simplicity (one parameter, no output schema), the description covers the purpose and a key constraint. However, it lacks information on return values, idempotency, or effects on other components, which would be helpful for full contextual understanding.
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 provides 100% coverage of the projectPath parameter with its description. The tool description adds no further meaning to the parameter, so the baseline 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 ('remove') and the resource ('all indexed context artifacts for a project from the vector database'). It is specific and distinct from sibling tools like codebase_context_index or codebase_context_search, which focus on indexing or searching.
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 explicitly notes that the tool is blocked during indexing and recommends using codebase_stop or waiting, providing clear when-not-to-use guidance. However, it does not elaborate on typical use cases for removal itself.
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 full burden. It lists what information is returned (definition, kind, callers, etc.) but does not mention if the tool is read-only, performance implications, or authentication needs. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that are front-loaded with the core purpose. No wasted words, though could hint at output format without adding length.
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?
Despite no output schema, the description lists key return fields. It adequately covers the tool's functionality for a symbol inspection tool. Could mention output format or data structure for full 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?
Schema coverage is 100% with descriptions for each parameter. The description adds context like 'confidence levels' not in schema, but does not elaborate further on parameter usage beyond what the schema provides. 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 clearly states it provides a '360° view' of a symbol including 'definition, kind, callers, callees, confidence levels', and explicitly says to 'understand a function or class before changing it', differentiating it from sibling tools like codebase_search or codebase_flow.
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 explicitly says 'Use to understand a function or class before changing it', providing clear usage context. However, it does not explicitly mention when not to use it or name alternative sibling 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?
Description lists returned data (build progress, node/edge count, etc.) but does not explicitly state that it is non-destructive or safe. Without annotations, more direct disclosure of read-only behavior would improve 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?
Two sentences: first enumerates specific status fields, second provides usage guidance. Front-loaded and concise without extraneous detail.
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 1 parameter fully described in schema, no output schema, and no annotations, the description adequately covers the main outputs and usage context. Could mention error conditions (e.g., if graph not built) but overall sufficient.
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?
Only one parameter (projectPath) with schema description already covering absolute path. Description adds no additional semantics beyond the schema, 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?
Clearly states it checks status of code dependency graph, listing specific details (build progress, node/edge count, last built, cache status). Explicitly references sibling tool codebase_graph_build for polling, distinguishing it from other graph tools.
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?
Explicitly states to use for polling after codebase_graph_build. Does not mention when not to use or alternatives, but the context of sibling tools makes the usage clear.
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 provided, so description carries full burden. Lists return values and implies read-only, but does not explicitly state non-destructive behavior or other traits. Adequate but could be more explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with key information (what it returns) followed by usage direction. No redundancy.
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?
Covers main points: return values and usage trigger. No output schema, but description lists what is returned. Could be slightly more detailed (e.g., prerequisites), but sufficient for the tool's simplicity.
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 a clear description for the single parameter. Tool description adds no extra meaning beyond schema, so 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?
Description clearly states verb ('check') and resource ('index status'), listing specific return values (chunk count, progress %, etc.). It distinguishes itself from siblings by indicating it is used after codebase_index for polling.
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?
Explicit instruction to call after codebase_index to poll until 100% complete gives clear context. No alternative tools mentioned, but the usage scenario is well-defined.
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?
Without annotations, the description carries the full burden. It accurately describes the read-only operation of listing artifacts and their properties. However, it does not mention potential prerequisites (e.g., file must exist) or error conditions, which would improve 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 (two sentences) with no wasted words. It front-loads the core action and resource, then provides a use-case hook. Every 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?
For a simple listing tool with one optional parameter and no output schema, the description is complete: it states the source, output fields, and purpose. No additional details are necessary for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema covers 100% of parameters (only projectPath) with a clear description. The tool's description adds no extra meaning about the parameter beyond what the schema provides, 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 verb 'List' and the specific resource 'context artifacts defined in .socraticodecontextartifacts.json', with examples of content types and output fields. It distinguishes from siblings like codebase_context_search by focusing on listing all items.
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 to discover project knowledge beyond source code, but does not explicitly state when not to use this tool or provide alternatives. There is no guidance on prerequisites or comparison with sibling tools like codebase_context_search.
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 provided, so the description carries the full burden. It explains the indexing, chunking, and embedding process but omits details like response format, potential side effects (e.g., overwriting existing index), or performance implications. Adequate but not comprehensive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no extraneous information. The action and resource are stated first, followed by supplemental detail and usage note. Efficient 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 tool with one parameter and no output schema, the description covers purpose, usage, and key behavioral context. It could mention that indexing might be a long operation or that errors may occur, but overall it is sufficiently 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 parameter 'projectPath' is documented in the schema. The description adds context about the configuration file but does not directly elaborate on the parameter beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Index or re-index') and the specific resource ('context artifacts defined in .socraticodecontextartifacts.json'). It also differentiates from the sibling tool 'codebase_context_search' by noting that tool auto-indexes.
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 'Usually not needed' and explains when to prefer 'codebase_context_search' because it auto-indexes on first use. Provides clear guidance on usage vs. 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 shoulders full behavioral disclosure. It reveals that the tool runs asynchronously ('Runs in the background') and directs the user to a polling mechanism. This is critical behavioral info. It does not mention resource usage, error behavior, or prerequisites, but the async nature is a key transparency point.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with zero wasted words. It front-loads the core purpose, then adds the crucial async behavior and guidance. Every sentence earns its place.
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 no output schema and no annotations, the description covers the primary concerns: what the tool does, that it's async, and how to monitor completion. It omits error cases, time estimates, and prerequisites, but for a straightforward build action, this is sufficient. The mention of a companion status tool adds important 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 100%: both parameters (projectPath, extraExtensions) are described in the schema. The description adds no extra meaning beyond what the schema already provides. Baseline of 3 is appropriate as the description does not degrade understanding but also doesn't enhance it.
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 verb ('Build'), resource ('dependency graph'), and method ('static analysis (ast-grep)'). It specifies what relationships are mapped (import/require/export) and differentiates from sibling tools like codebase_graph_query (query) and codebase_graph_status (poll). This leaves no ambiguity about the tool's function.
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 tells the user to call codebase_graph_status to poll progress since the build runs in the background. This provides a clear workflow step. However, it does not explicitly state when to use this tool versus other graph-related siblings (e.g., when to build vs. query), but the context of 'Build' vs 'Query' is implicitly clear from 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?
Without annotations, the description covers key behavior: waiting for in-flight builds and the option to rebuild. It does not detail permissions or side effects, but 'remove' implies destruction, which is adequately communicated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two efficient sentences, front-loaded with the primary action, and no redundant information.
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 single-parameter tool with no output schema, the description covers the purpose, notable behavior (waiting for builds), and post-removal options. Minor omission: does not explicitly state that the graph is deleted upon removal, but this is implied.
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?
With 100% schema coverage, the schema already documents the lone parameter ('projectPath'). The description adds no further detail beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool removes a project's persisted code graph and distinguishes it from siblings like codebase_graph_build (rebuild) and codebase_graph_status (status check).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool (to remove a graph) and mentions that it waits for in-flight builds, providing context. However, it does not explicitly contrast with alternatives like codebase_graph_visualize or codebase_graph_query.
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 provided; description lists checked components but does not disclose whether it modifies state, requires permissions, or what the output format is. Adequate for a read-only health check but lacks 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?
Two concise sentences, front-loaded with action and scope, zero wasted 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?
Given no parameters and no output schema, description covers the tool's purpose and components. Could mention return value but not required for such a simple health check.
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 (schema coverage 100%), so description need not add parameter details. Baseline for 0 parameters is 4.
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 it checks health of specific infrastructure components (Docker, Qdrant, Ollama, embedding model) and is used to diagnose setup issues. Distinct from sibling tools.
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?
Explicitly says 'Use this to diagnose setup issues', providing clear context for when to invoke. No explicit when-not or alternatives, but siblings do not overlap.
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?
Given no annotations, the description discloses key behaviors: incremental update, synchronous execution, and dependency on file changes. It does not detail side effects or failure modes but is reasonably transparent for a maintenance tool.
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?
Extremely concise with three short sentences. Each sentence adds value: action, scope, synchronicity, and a usage caveat. No unnecessary 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?
Covers purpose, behavior, and a key usage guideline. Missing details like prerequisites (must have an existing index?) or error handling, but for a simple update tool with optional parameters and no output, it is largely 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%, so the schema already documents both parameters. The description adds no extra context or constraints beyond what the schema provides, meeting the baseline but not exceeding it.
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 incrementally updates a codebase index, specifically re-indexing only changed files. It distinguishes itself from a full re-index (implicitly) and from the file watcher by noting it is usually not needed if the watcher is active.
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?
Provides clear guidance: 'Runs synchronously' and 'Usually not needed if file watcher is active' informs when to use or avoid the tool. However, it does not explicitly contrast with sibling tools like codebase_index or codebase_watch, missing a direct alternative.
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 fully bears the transparency burden. It discloses key behaviors: stopping watcher, canceling indexing with drain, waiting for graph build. No contradictions or missing critical behaviors.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: first states purpose, second adds behavioral details. Every sentence earns its place with 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 one parameter, no output schema, and no annotations, the description provides sufficient detail on purpose, behavior, and parameter meaning. It is complete for a simple removal 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 the description adds no extra meaning beyond the schema's parameter definition. 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 removes a project's codebase index from the vector database, using a specific verb and resource. It distinguishes from sibling tools like codebase_context_remove and codebase_graph_remove.
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 explains that the tool safely stops the file watcher, cancels indexing, and waits for graph build, implying context for use. However, it does not explicitly mention when not to use or compare to alternatives like codebase_stop or codebase_context_remove.
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 exist, so description carries the burden; it clearly defines the operation as listing/searching (likely read-only) and adds context about discovery, but lacks explicit mention of side effects or safety 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?
Two sentences, no redundancy, front-loaded with purpose and usage context; every word adds value.
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?
Tool has 4 parameters all described, but no output schema or return format info; description doesn't detail what the list contains (e.g., symbol names/types), leaving slight ambiguity for agents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so baseline is 3; description does not add new parameter details beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it lists symbols in a file or searches by name across the project, and distinguishes from sibling tool codebase_symbol by noting it's for discovery before drilling in.
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 (before drilling into a single symbol) and names the alternative tool (codebase_symbol), providing clear guidance on usage context.
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 are provided, so the description carries the full burden. It discloses that with no args it returns a ranked list of auto-detected entry points, and with entrypoint it returns a call tree. It mentions depth default and max, which is behavioral. There is no mention of side effects, but tracing is inherently read-only, and the description is transparent about the behavioral difference.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, both dense with information. The first sentence states the core purpose with a clarifying question, and the second explains the no-args vs entrypoint behavior. Every sentence earns its place with no waste.
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 4 optional parameters, no output schema, and no annotations, the description adequately explains the tool's behavior: listing entry points or tracing a call tree. It could mention the output format briefly, but for a tracing tool with clear intent, it is sufficiently complete.
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?
Schema coverage is 100%, but the description adds value beyond the schema by explaining the behavior difference based on entrypoint presence, default depth of 5, and max 10. It clarifies that file is a disambiguation hint, which aligns with the schema. This goes beyond the baseline 3.
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 traces execution flow forward from an entry point, returning a call tree. It distinguishes between no arguments (returns auto-detected entry points) and with entrypoint (returns call tree). It names conventional entry points (main(), framework routes, tests), and the purpose is distinct from siblings like codebase_symbol or codebase_graph_query.
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 explains when to omit entrypoint (to list entry points) and when to provide it (to trace). It does not explicitly mention alternatives or when not to use, but the context is clear enough for an agent to decide based on whether they need to discover entry points or trace a specific one.
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 discloses polymorphic behavior based on target format and that it lists files/functions that could break. It doesn't detail output format but provides adequate transparency for the tool's 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?
Three sentences with clear structure: purpose, polymorphic behavior, usage recommendation. No unnecessary words or repetition.
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?
Comprehensive for a tool with 3 parameters and no output schema or annotations. Covers when to use, how target works, and key behavior. Could mention output format, but not essential.
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?
Adds meaning beyond schema by explaining polymorphic nature of 'target' (path-like vs. name-like). Schema already describes each parameter, so this provides useful clarification.
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: 'return the BLAST RADIUS for a file or symbol' and lists what it returns. It distinguishes itself from siblings like codebase_symbol and codebase_context by focusing on impact analysis for refactoring.
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?
Explicitly advises 'Use this BEFORE refactoring, renaming, or deleting code', providing clear when-to-use guidance. While it doesn't mention when not to use, the context is sufficient for selection among sibling tools.
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?
Discloses asynchronous behavior, immediate return, progress polling, and concurrency handling. Lacks detail on side effects like resource consumption or permission requirements, but sufficient given no annotations.
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?
Three concise sentences, front-loaded with the core action, no redundant information.
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?
Covers the main workflow (start, poll, wait) and edge case (already indexing). Missing explicit return value format and error handling, but sufficient for a simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with clear parameter descriptions. The tool description adds no extra semantics beyond the schema 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 clearly states the tool starts indexing a codebase in the background, returns immediately, and distinguishes from siblings by referencing codebase_status for progress polling and advising against searching until complete.
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 codebase_status for polling, not to use search during indexing, and what happens if already indexing, providing clear exclusions and 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?
No annotations provided, so the description bears the full burden. It indicates that the tool returns relevant code chunks without modifying the codebase, implying a read-only operation. However, it does not explicitly state that it is non-destructive or mention any potential side effects or error conditions. This is fairly transparent but leaves some ambiguity.
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 consists of two concise sentences. The first sentence states the purpose, and the second provides a crucial usage condition. No unnecessary words. Well-structured and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has 7 parameters and no output schema. The description explains the overall purpose and a key precondition. However, it does not describe the output structure (e.g., what fields are returned in code chunks) or any error handling. Given the complexity of the parameters, the description might benefit from more detail, but it covers the essential usage 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?
The input schema covers all 7 parameters with detailed descriptions, including defaults and environment variable overrides for some. The tool description does not add additional parameter semantics beyond what the schema provides. Baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it performs semantic search and returns code chunks matching a natural language query. It distinguishes from sibling tools by specifying the precondition of indexing, making the purpose specific and 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 states to only use after codebase_index is complete and recommends checking codebase_status first. This provides clear when-to-use conditions and a prerequisite check, which helps the agent avoid errors.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It states 'Display information', indicating a read-only operation with no side effects, which is transparent. No additional behavioral details needed given the tool's simplicity.
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: two sentences, no wasted words. It is front-loaded with the main action and use case.
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 no parameters, no output schema, and the description provides both action and usage context, it is fully complete for an overview tool.
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 0 parameters, so schema coverage is 100%. Baseline for 0 parameters is 4. The description does not add parameter info because none exist, and it is clear about the tool's 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 clearly states the verb 'Display' and the resource 'information about SocratiCode, its tools and how to use it'. This distinguishes it from sibling tools which focus on specific codebase operations.
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 explicitly says 'Use this to get a quick overview of the MCP tools and their purpose', providing clear context for when to use this tool. However, it does not mention when not to use it or 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?
No annotations provided, so description carries full burden. It explains the graceful stop behavior, that the current batch finishes and checkpoints, preserving progress. This is informative and sets proper 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?
Two concise sentences with no wasted words. Front-loaded with the main action. Every 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?
Given no output schema and a simple stop action with one optional parameter, the description is complete. It covers what happens during stop and what to do next (resume with codebase_index).
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?
One parameter 'projectPath' with full description in schema. Tool description does not add additional meaning beyond what schema already provides. Schema coverage is 100%, so baseline 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?
Clearly states it stops an indexing operation gracefully. Verb 'stop' and resource 'indexing operation' are specific. Distinguishes from siblings like codebase_index (starts) and codebase_status (shows status).
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?
Implicitly says when to use: to stop an indexing operation. It also explains that after stopping, you can resume with codebase_index. Does not explicitly mention when not to use or alternatives, but the purpose is clear and targeted.
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. It thoroughly discloses behavioral traits: color-coding, circular dependency highlighting, browser auto-open, headless fallback, interactive features like click/right-click actions, and layout switchers. No contradictions.
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 two paragraphs and bullet points for modes. It is front-loaded with the main purpose. Every sentence adds value, though some interactive details could be more concise.
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 complexity of the tool (two modes, many interactive features) and no output schema, the description fully covers return values (Mermaid string, HTML file path) and key interactive behaviors. It is complete for an agent to select 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?
Schema coverage is 100% with descriptions for all 3 parameters. The description adds value by clarifying default mode and the effect of the `open` parameter (e.g., headless use), which goes beyond the schema's minimal descriptions.
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 visualizes the code dependency graph and explicitly distinguishes two modes with specific outputs (Mermaid text vs interactive HTML). This differentiates it from sibling tools like codebase_graph_stats or codebase_graph_query.
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 guidance on when to use each mode: mermaid for inline rendering, interactive for visual exploration. It implies context of use but does not explicitly exclude scenarios or contrast with alternatives like codebase_graph_query.
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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