infimium

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by infimium-ai

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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

Latest release: v0.5.8
Disambiguation5/5
Each tool targets a clearly distinct function: context reading, health probe, web search, URL fetching, local docs, semantic code search, symbol expansion, dependency graph, shell execution, planning, and project memory. There is no overlap or ambiguity between them.
Naming Consistency2/5
Naming is inconsistent: some tools use verb_noun (web_search, fetch_url, expand_symbol), while others are bare nouns (shell, plan), abbreviations (dep_graph), or greetings (hello_infimium). This mixed style makes the set harder to predict and navigate.
Tool Count5/5
With 11 tools, the server is well-scoped—each tool earns its place and the count is within the ideal 3-15 range. It feels comprehensive without being bloated.
Completeness4/5
The tool surface covers a broad workflow: context, code exploration, web/docs lookup, shell access, planning, and memory. Slight gaps like a direct file editor exist, but shell can fill in, so the coverage is nearly complete.
Average 2.8/5 across 11 of 11 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- 1 of 1 community issues answered or closed in the last 6 months
- 65 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
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 provided, the description carries the full burden of behavioral disclosure. It only states 'Query indexed local documentation' without indicating whether the operation is read-only, what setup is required, or what the response contains. This is a significant gap for a query tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise, but it is under-specification rather than effective conciseness. It fails to include necessary usage and parameter details, so the brevity is not a benefit.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
This tool has three parameters, no annotations, and no output schema. The description is far from complete: it does not clarify what 'indexed' means, how project_path scopes the query, or what top_k controls. The tool cannot be used reliably based on this description alone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description provides no parameter explanations. The agent must infer meanings for query, top_k, and project_path from names alone, which is insufficient for correct invocation.
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 with a specific verb ('Query') and resource ('indexed local documentation'), distinguishing it implicitly from siblings like web_search and semantic_code_search. However, it does not explicitly contrast with alternatives, so it stops short of a perfect score.
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 offers no guidance on when to use this tool versus alternatives. There is no mention of prerequisites, exclusions, or a preferred context, leaving the agent to guess.
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 present, so the description carries the full burden. It implies a read-only inspection but does not disclose return format, whether traversal is transitive, required permissions, or failure modes. The word 'inspect' hints at non-mutating behavior, but no explicit guarantees are given.
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 front-loaded sentence, which is efficient, but it omits essential information. True conciseness balances brevity with necessary detail; this veers into under-specification.
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 that there is no output schema, no annotations, and only vague parameter descriptions, the tool description is insufficient for an agent to use it effectively. It lacks details about return values, edge cases, or relation to sibling tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description adds nothing about the parameters. An agent cannot determine what 'symbol_name' should look like (e.g., fully qualified name or plain string) or what 'project_path' means or its default behavior when omitted.
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 'Inspect dependency relationships for a symbol' uses a clear verb ('inspect') and identifies a specific resource ('dependency relationships for a symbol'). It distinguishes this tool from siblings like semantic_code_search or expand_symbol, though it does not specify whether it shows incoming or outgoing dependencies.
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 its siblings. There is no mention of alternatives, exclusions, or typical use cases, leaving the agent to guess based on the name alone.
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 the full burden of disclosing behavioral traits, but it only says 'Run an allowlisted shell command.' It fails to mention potential side effects, output format, error handling, security implications, or the fact that this could modify the system. 'Allowlisted' hints at some restriction but lacks detail, leaving significant ambiguity for a powerful tool.
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 concise—a single sentence with no fluff—which is positive. However, it is under-specified to the point of being almost unhelpful. Concision is valued, but here it sacrifices necessary detail, making it only minimally acceptable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that this tool executes arbitrary system commands, the description is critically incomplete. It lacks information about the execution environment, command output, exit codes, security restrictions, timeout behavior, and interaction with 'cwd'. With no annotations or output schema, the description fails to provide a complete picture, making safe and effective use nearly impossible.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not compensate. Parameters like 'cwd', 'timeout', and even 'command' are not elaborated in any way. The description doesn't clarify that 'command' is the executable string, 'cwd' sets the working directory, or 'timeout' limits execution time. This leaves users without meaningful guidance on how to structure invocations.
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 primary function: to run a shell command. The verb 'Run' is action-specific and 'shell command' identifies the resource. While it doesn't elaborate on what 'allowlisted' entails, it distinguishes itself from siblings like web_search or fetch_url, which perform other actions.
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 doesn't mention scenarios like executing system-level commands or interacting with the local environment, nor does it specify any prerequisites or exclusions. Users are left to infer its context from the tool name alone.
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 says 'current information' but does not describe result formats, pagination, rate limits, or what kind of web sources are searched. The description is too vague to be informative.
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, concise sentence that is front-loaded and easy to parse. It does not waste words, but the brevity comes at the cost of missing useful behavior and parameter details.
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 there is no output schema and no annotations, the description should explain return values and common use cases. It does neither, and also lacks usage context compared to its sibling tools. The description is too minimal for an agent to confidently invoke the tool in varied scenarios.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage for parameters, and the description does not mention 'query' or 'max_results' at all. Since the parameter names are somewhat self-explanatory but not guaranteed, the lack of any explanation leaves the agent to guess their exact semantics and constraints.
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 'Search the web for current information' clearly states the action (search) and resource (the web), making it easy to understand what the tool does. However, it does not explicitly differentiate itself from sibling tools like fetch_url or query_local_docs, so it stops 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 no guidance on when to use this tool versus alternatives. It does not mention scenarios like needing fresh information, distinguishing from local document search, or say when not to use it. This is a clear gap.
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?
There are no annotations, so the description carries the full burden of behavioral disclosure. It does not mention possible failures (e.g., invalid URLs, network errors, redirects), rate limits, authentication requirements, or the structure/format of the returned content. This is a significant gap for a network-fetching 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 concise sentence, front-loaded with the core action. It is easy to scan and understand the primary purpose. However, the brevity sacrifices important behavioral and usage details, so it is not perfectly complete for the tool's complexity.
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 that there is no output schema and no annotations, the description needs to provide more context about what the agent should expect. It does not describe the return structure, error handling, or what formats 'extractable content' may take. For a simple tool with only two parameters, the description is under-specified and leaves too much to inference.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only indirectly references the 'url' parameter ('Fetch a URL') and the 'extract' action ('extract readable content'). It does not explain the two parameter names, the enum choices for 'extract', or the default behavior. The schema provides the default and enum, but the description adds little semantic value beyond what the parameter names imply.
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 'Fetch' and clearly identifies the resource ('a URL'), with the added action of extracting readable content. It is distinguishable from sibling tools like 'web_search', which implies a search-based retrieval rather than direct fetch of a specified URL. However, it does not explicitly state what 'readable content' includes, 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?
No guidance is provided on when to use this tool versus alternatives like web_search or get_context. There are no exclusions, prerequisites, or preferred scenarios. The description simply states the action, leaving the agent to infer when it is appropriate.
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 disclosing behavioral traits. It does not mention potential side effects such as writing files (write_plan, output_path) or the ability to run in dry-run mode (dry_run). The tool also supports custom languages and project paths, none of which are disclosed, leaving significant behavioral ambiguity.
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 concise sentence, which is structurally efficient and front-loaded. However, for a tool with 7 parameters and multiple behavioral options, this is under-specified—a complete description would need more detail to be appropriately sized. It is not excessively verbose, but the lack of substance makes it minimally adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (7 parameters, no annotations, no output schema), the description is drastically incomplete. It does not explain what a 'grounded implementation plan' entails, how the plan is generated, whether the tool returns a string or writes a file, or how parameters like dry_run and write_plan alter behavior. An agent would have insufficient context to invoke this tool reliably.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 7 parameters with 0% description coverage, and the tool description does not mention any of them. It fails to explain what 'task' means, what 'top_k' controls, or that 'language' and 'project_path' affect scope. The description provides no semantic value beyond the schema's raw field names, making parameter understanding entirely dependent on the agent's prior knowledge.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Generate') and object ('grounded implementation plan') scoped to 'the current repository.' It distinguishes itself from sibling tools like semantic_code_search or dep_graph, which serve different functions.
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 'grounded implementation plan' implies it should be used when planning based on repository context, but it does not explicitly state when to use this tool over alternatives like get_context or shell. No exclusions or alternative recommendations are provided, so guidance is inferred rather than explicit.
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 does disclose that the output is 'compact symbol signatures', which is a meaningful behavioral trait. However, it does not state whether the operation is read-only (though it is implied), nor does it mention any limitations, performance characteristics, or underlying mechanisms (e.g., embeddings). This is minimal but not completely absent.
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 words. It directly states the action and the result. Every word earns its place, and it is appropriately brief for a tool whose core purpose is clear from its name.
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 tool has 4 parameters, no annotation, and no output schema. The description is too sparse to provide complete guidance for an agent. It does not explain the parameters, return format details, or when to use the tool. For a search tool with multiple optional filters and a specific output type, this level of completeness is clearly insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description contains no parameter information. The description does not explain what 'query' means beyond the tool's general purpose, nor does it define 'top_k', 'language', or 'project_path'. Since the schema provides no property descriptions either, the agent must infer all parameter semantics from the tool name alone, which is insufficient.
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: semantically searching code and returning compact symbol signatures. It specifies a verb ('search'), a resource ('code'), and a mode ('semantically'), which distinguishes it from keyword search. While it does not explicitly name sibling tools, the tool's focus on semantic code search sets it apart from web_search, query_local_docs, and expand_symbol.
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 prerequisites (e.g., indexing), exclusions, or any context for choosing semantic_code_search over other search or code-related tools. The usage context is only implied by the tool's name and generic description.
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 names operations like remember, complete/archive, and search, but does not explain side effects, persistence semantics, return values, or any prerequisites. This is insufficient for a tool with multiple mutating actions.
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 primary purpose and lists key actions without fluff. It is efficient and appropriate in size for a high-level overview.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness1/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (11 parameters, multiple action modes, no output schema, no annotations), the description is far too incomplete. It provides only a high-level summary and omits critical usage details, action-specific semantics, and expected responses.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0% and the description provides no parameter-level information. The tool has 11 parameters, including enums and defaults, but none are explained, leaving agents unable to construct valid calls.
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 manages compact project memory across chats, agents, and IDEs, and enumerates specific operations (remember, complete/archive, search, update rules). It distinguishes from sibling tools by focusing on memory management, though 'manage' is a generic verb and the exact resource is broad.
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 the tool should be used when needing to maintain project memory across chats, agents, and IDEs, providing clear context for when to use it. It does not explicitly mention alternatives or exclusions, but the context is specific enough to guide 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 should disclose whether the tool is read-only, what it returns, or if it has side effects. 'Health probe' implies safety but does not explicitly confirm behavior, response format, or error conditions. This is a significant gap for a tool with no structured 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?
The description is a single short sentence that conveys the essential purpose without wasted words. For a zero-parameter health probe, this level of conciseness is appropriate.
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 tool is simple (no params, no output schema, no annotations), but the description still omits key context such as the return value (e.g., OK/status), potential errors, and whether any setup is required. It feels incomplete for an agent deciding whether to invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline is 4. There is nothing for the description to explain regarding parameters, and no schema-description coverage issues exist.
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 identifies the tool as a 'health probe' for the Infimium MCP server, which clearly indicates its purpose. It is distinct from sibling tools like web_search or shell, though it lacks an explicit verb like 'checks' or 'returns'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus alternatives, no prerequisites, and no mention of typical scenarios. The description is purely declarative.
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 the full burden of transparency. It only states the action 'load the full implementation' but doesn't disclose what exactly is returned (e.g., source code, metadata), whether it requires a project path or file path for disambiguation, or any error behavior. The one-line description lacks essential behavioral context.
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 with no filler words. It clearly states the purpose and the workflow context, 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?
The tool has no output schema and no annotations, so the description must cover both input parameters and return behavior. It fails to explain the role of optional parameters, what 'full implementation' includes, or how the returned data is structured. While simple, the lack of context around optional file_path and project_path leaves the agent guessing.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for the three parameters. It doesn't explain what file_path and project_path mean or how they relate to symbol_name. The description only mentions 'one symbol', leaving the optional parameters completely undocumented, which is insufficient for an agent to correctly populate them.
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 'Load' with a clear resource 'full implementation of one symbol', and explicitly ties it to symbols returned by semantic_code_search. This distinguishes it from sibling tools like semantic_code_search (search) and dep_graph (dependencies).
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 phrase 'returned by semantic_code_search' provides a clear workflow context: this tool should be used after obtaining a symbol from semantic_code_search. However, it doesn't explicitly state when not to use it or mention alternative tools, so it falls short of a full 5.
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 must carry behavioral disclosure. It does disclose that passing project_path activates the IDE workspace as default, a side-effectful behavior, and uses 'Read' to signal a non-mutating operation. It does not explain refresh/format defaults or whether any re-indexing occurs, but it avoids contradiction.
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: the first states purpose with specific content, the second gives a concise setup instruction. No redundant filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description gives a solid purpose and one parameter's behavior, but without annotations or output schema it leaves gaps: it does not describe the output format/length or how refresh/limit alter results, and it lacks guidance relative to sibling tools. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description only adds semantics for project_path ('activate the current IDE workspace as the default'). It does not explain the meaning or effect of limit, format, or refresh, leaving the agent to infer from the schema alone.
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 specifies a clear action ('Read') and a concrete resource ('balanced YAML context layer') with listed contents (repo overview, Git state, task, memory, AST-first handoff guidance). It is not a tautology and conveys a distinct purpose, though it does not explicitly contrast with sibling tools like project_memory.
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?
It clearly implies when to use it — when you need repo overview, Git state, task, memory, or handoff guidance — and includes a practical activation instruction ('Pass project_path once...'). However, it does not provide explicit exclusions or alternative tool recommendations, so it stops short of the strongest guidance.
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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