6amdev-server-mcp

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by 6amdev

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Tools are grouped by domain (system, docker, gitea, ollama, workspace, claude) which makes them fairly distinct. However, the system_* and docker_* tools have some overlap in purpose (e.g., system_status vs docker_stats both report resource usage), which could cause minor confusion for an agent.
Naming Consistency4/5
All tool names use a consistent pattern of domain_prefix_action (e.g., docker_list, gitea_issues). This makes the set predictable. Minor inconsistency: the workspace tools use git as part of workspace_git rather than git_*, and claude tools are not prefixed uniformly (e.g., claude_ask vs claude_status).
Tool Count3/5
With 34 tools, the server covers six domains, but this is on the heavy side for a single server. The claude and ollama domains add 5-6 tools each which feels excessive given that many tasks could be combined (e.g., claude_ask, claude_task, claude_review, claude_explain all serve similar purposes with vague boundaries).
Completeness3/5
Each domain has reasonable coverage: system has monitoring, docker has basic lifecycle, gitea has listing and issue creation, ollama has model management. Notable gaps: gitea lacks repo creation/update/deletion and commit reading; workspace lacks file deletion or listing by type; no tool for restarting services or managing users.
Average 3.2/5 across 34 of 34 tools scored. Lowest: 2.4/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository includes a README.md file.
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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.
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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

Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description must fully disclose behavior. It only says 'Run a prompt', omitting whether the operation is synchronous, streaming, has side effects (e.g., model loading), requires network, or consumes tokens. This is a critical gap for an AI agent deciding to invoke the 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 single sentence is technically concise but too brief to be helpful. It primarily restates the function name ('Run a prompt with an Ollama model') without earning its place through additional context. A more informative structure (e.g., listing key behavior points) would be appropriate for a 3-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is insufficiently complete. It does not cover return value format (raw text vs JSON), error handling, timeout behavior, or prerequisites (model must be pulled first). The tool is simple but needs more context for safe invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with descriptions for all three parameters, so baseline is 3. The tool description adds no extra meaning beyond the schema (e.g., does not explain the interplay between system and prompt, or model naming conventions). Thus it meets but does not exceed the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (run) and the resource (a prompt with an Ollama model). While it distinguishes from other Ollama siblings (list, pull, delete), it does not differentiate from the claude_ask tool which also runs prompts but with a different backend.
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 ollama_run versus sibling tools like ollama_pull (to ensure model is available), ollama_status (to check readiness), or claude_ask. The description lacks any conditional advice or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden for behavioral disclosure. It only states the action without revealing side effects (e.g., what if container is already running? Are there permissions required? Does it block until started?). This is a severe gap for a mutation operation.
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 short sentence, which is concise but at the cost of completeness. It earns its place (no fluff) but could front-load additional context like prerequisites or return behavior in the same space. It is minimally adequate.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (1 param, no output schema) and lack of annotations, the description is incomplete. It omits crucial context: what state the container must be in, what happens on error, and whether the operation is asynchronous. A more complete description would aid proper usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% (one parameter 'container' with description). The tool description adds no further meaning beyond what the schema already provides. Per guidelines, baseline is 3 when schema coverage is high, and description doesn't detract or add significantly.
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 'Start a Docker container' clearly states the action and resource. It distinguishes from sibling tools like docker_stop, docker_restart, and docker_list. However, it could be more specific (e.g., 'start a stopped container') to avoid ambiguity with 'create' or 'run'.
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 on when to use this tool versus alternatives like docker_exec (run commands), docker_logs (view output), or docker_stats (monitor). The description does not specify prerequisites (e.g., container must exist) or conditions for use, leaving the agent to infer context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only says 'Stop', which implies a state change but omits details like whether it forces or gracefully stops, return behavior, permission requirements, or side effects (e.g., terminating processes).
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 extremely short (3 words), but this sacrifices valuable context. It is under-specified rather than efficiently informative. Every sentence should earn its place; here, the name alone would suffice.
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 no output schema and simple parameters, the description lacks details about return values, error conditions (e.g., container not found, already stopped), and post-conditions. An agent cannot fully gauge the effects or safety of using this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% for the single parameter, which already describes 'container' as 'Container name or ID'. The tool description adds no additional meaning beyond the schema, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description is a specific verb+resource ('Stop a Docker container'). It clearly differentiates from siblings like docker_start or docker_restart based on the operation name, though it does not explicitly contrast with them.
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 vs alternatives (e.g., docker_stop vs docker_restart, or stopping via docker_exec). There is no mention of prerequisites (e.g., container must be running) or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description carries full burden. It only says 'list'—implying a read operation—but fails to disclose authentication needs, pagination, rate limits, or whether results are limited to the user's accessible repos. A listing tool should at least note any default constraints.
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 extremely short (one sentence) which is concise, but it sacrifices necessary detail. It lacks structure and feels incomplete rather than efficiently minimal.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should give an idea of return format. It does not. The optional owner parameter is not mentioned in the description, so an agent doesn't know the scope of 'all'. This is insufficient for a tool with one parameter and no other structured hints.
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% (owner parameter has a description). The tool description adds no extra meaning beyond the schema. Baseline 3 is appropriate since the schema already explains the parameter, but the description does not enhance understanding.
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 'List all repositories from Gitea', using a specific verb and resource. It distinguishes from sibling tools like gitea_repo_info (single repo) and gitea_issues (issues). However, it's vague about scope—does 'all' mean all accessible repos or all in the instance? A more precise statement would be ideal.
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 gitea_repo_info for a single repository. The description is a single sentence with no context about prerequisites, filtering, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It does not mention read-only nature, authentication requirements, rate limits, output format, or any side effects. The description only states the basic purpose, leaving the agent without crucial 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.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, which is concise but not optimally informative. It front-loads the core purpose but omits details that could be provided without much length (e.g., default line count, example services). It is adequate but not exemplary.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is simple (2 params, no output schema), the description should cover basic expectations. It fails to mention output format, pagination, or maximum lines. The agent lacks enough context to use the tool effectively without supplementing from the schema alone.
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. The description adds no additional meaning beyond the schema. It does not explain default values for 'lines' or enumerate valid service names. Since the schema already fully documents the parameters, the description is not penalized further but adds no value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (view) and the resource (system logs for a specific service). The verb 'view' and the resource 'system logs' are specific. However, it does not differentiate from sibling tools like docker_logs, which also view logs but for a narrower scope. Without this distinction, an agent might not know when to choose system_logs over docker_logs.
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 vs. alternatives (e.g., docker_logs for Docker-specific logs). No when-to-use or when-not-to-use context is provided. The description implies it's for any system service but doesn't specify use cases or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must disclose behavioral traits. It only says 'search for files or content', omitting crucial details like whether the operation is read-only, what the return format is (list of paths, snippets), search recursion, pattern syntax, or performance implications. The description is insufficient for safe and correct invocation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with no wasted words, but it is under-informative. Essential details are omitted in favor of brevity. Front-loading is acceptable ('Search...' verb first), but the conciseness reduces overall value.
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 3 parameters, no output schema, and no annotations, the description should explain return values, scope, and behavior. It fails to mention whether results include file paths, content snippets, or just counts. A search tool with type and path options needs more context than provided to be reliably useful.
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 with descriptions, so the baseline is 3. The description adds no extra meaning beyond what the schema already provides (e.g., query, path, type). It does not clarify supported pattern syntax for 'query' or what 'content' search entails (e.g., full-text vs. substring).
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Search for files or content in the workspace' clearly identifying the verb (search) and resource (files/content). However, it does not differentiate itself from sibling tools like workspace_list or workspace_tree which also interact with files. The purpose is clear but lacks distinction.
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 guidelines are provided about when to use this tool versus alternatives such as workspace_list, workspace_tree, or workspace_read. There is no mention of when not to use it or the context in which it is most appropriate. This forces the agent to guess based solely on the name.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full behavioral burden. It only states 'Returns AI-generated response', which is obvious. It omits critical traits: whether the call is read-only, if it has side effects, requires prior context, or has rate limits.
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 convey purpose and output. No filler or repetition; every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no output schema and siblings that specialize (e.g., claude_explain, claude_review), the description lacks enough detail to help an agent select it confidently. It does not describe return format, question scope boundaries, or how to leverage the optional project parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents both parameters. The description adds no parameter-specific meaning (e.g., how to format the question, what 'project' does for context). Baseline score of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Ask' and resource 'Claude Code', specifying the domain as 'code, architecture, or development'. It implies a general Q&A role among sibling tools like claude_review and claude_explain, but does not explicitly differentiate them.
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 on when to use this tool versus alternatives (e.g., claude_explain for explanations, claude_review for review). The description does not mention prerequisites, contexts, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears full responsibility for behavioral disclosure. It only states 'List Docker images' with no information about side effects, connection requirements, idempotency, or return format. Essential traits are completely 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, focused sentence that contains no redundant words. It is front-loaded and efficient, appropriate for the simplicity of the tool.
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, the description does not explain what the returned list contains (e.g., image IDs, names, tags). No context about dependencies (e.g., Docker daemon) is provided. The tool is simple, but the description leaves agents guessing about output structure.
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?
With 0 parameters and 100% schema coverage, the baseline is 4. The description adds no param-specific detail, but the schema is already empty. The brief description is adequate for a parameterless tool.
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 'List Docker images' clearly states the action and resource, using specific verb and noun. It distinguishes from sibling tools like docker_stats or docker_start, though docker_list is ambiguous and could overlap.
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 like docker_list or docker_stats. No exclusions, prerequisites, or context about selection criteria are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must disclose behavioral traits such as read-only nature, rate limits, or pagination behavior. It only says 'List issues', which implies read operation but does not confirm safety, pagination, or any side effects. The description is too brief given the lack of annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence, making it highly concise. It is front-loaded with the action and resource. No extraneous content exists. However, it is so brief it sacrifices completeness, preventing a score of 5.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no annotations, and no output schema, the description should provide more context about return values, pagination, or ordering. It does not explain whether the list includes all issues or is paginated, nor what information is returned per issue. This leaves gaps for effective agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with all three parameters well-described in the schema (repo, owner, state). The description does not repeat schema details, which is acceptable. However, it does not add any extra context (e.g., behavior when state is omitted, or what 'all' includes). Baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (List) and the resource (issues in a repository). It is concise and unambiguous. However, it does not differentiate from sibling tools like gitea_create_issue or gitea_repo_info, so it loses a point for lack of distinction.
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 (e.g., gitea_repos for listing repos, or gitea_repo_info for repo details). It also does not mention any prerequisites or filtering scope (e.g., state defaults are in schema but not clarified in description). This leaves the agent without context for appropriate 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?
No annotations are present, so the description must fully disclose behavior. It implies a read-only operation ('Get') but does not explicitly state that no modifications occur, nor does it mention authentication requirements, rate limits, or what 'detailed information' encompasses. The behavioral disclosure is minimal.
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, front-loaded sentence with no wasted words. It is efficiently structured, though the conciseness comes at the expense of completeness in other dimensions.
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 low complexity (2 parameters, no output schema, no annotations), the description is too sparse. It does not explain what 'detailed information' includes, whether it is read-only, or how it differs from listing tools. The agent lacks key context for correct usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with both parameters ('repo' and 'owner') having clear descriptions in the schema. The description adds no additional semantics beyond what the schema already provides, so a baseline of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'Get' and the resource 'repository', clearly indicating a retrieval operation. It distinguishes from sibling 'gitea_repos' (likely a listing tool) by specifying 'detailed information' for a single repository, though it could explicitly state 'single repository'.
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 'gitea_repos' for listing or other sibling tools. There is no mention of prerequisites or context, leaving the agent without decision support.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must fully disclose behavior. It only states the action (delete) but omits critical traits: whether deletion requires the model to be stopped, whether it is reversible, error conditions, or permissions needed. This is a minimal and insufficient disclosure for a destructive operation.
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 zero redundant content. Every word contributes to conveying the tool's purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple delete operation with no output schema and no annotations, the description is insufficient. It lacks behavioral context (safety, prerequisites), meaning the agent cannot fully reason about the tool's usage. Information present in sibling tool names (e.g., ollama_status, ollama_list) could hint at preconditions, but the description itself is incomplete.
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% and the single parameter 'model' already has a clear description 'Model name to delete'. The tool description adds no new semantic value; it simply restates the action. Baseline score of 3 is appropriate given the schema does the work.
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 'Delete an Ollama model' uses a specific verb (delete) and clearly identifies the resource (Ollama model). It is immediately distinct from sibling tools like ollama_list, ollama_run, or ollama_pull.
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 or when not to use this tool. There is no mention of prerequisites (e.g., model not be running), alternatives, or typical workflows. The agent receives zero context for decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It correctly implies a mutation (executing a command can change container state), but it doesn't specify whether the command runs interactively, whether output is returned, or what happens if the container isn't running. A score of 3 is appropriate as the description is minimally adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence with no wasted words. It's front-loaded with the core action. However, it could be more structured by adding a second sentence for usage guidelines or return information, but it earns a 4 for being concise without being under-specified.
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 annotations and no output schema, the description is incomplete. A mutation tool like docker_exec should clarify output behavior (e.g., returns stdout/stderr), error handling (e.g., container not running), and lifecycle implications. The 2 parameters are well-covered by the schema, but the description doesn't help the agent understand execution semantics.
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 semantics beyond paraphrasing the tool's purpose. For example, it doesn't explain that 'container' can be either name or ID (schema says both), nor does it clarify if 'command' should include arguments or be a single executable path. Baseline 3 is correct.
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 'Execute a command inside a running container' clearly specifies the verb ('execute') and resource ('command inside a running container'). It distinguishes the tool from siblings like docker_start, docker_stop, and docker_logs, which manage container lifecycle or output, not command execution.
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. For example, it doesn't mention that the container must be running first (distinguishing from docker_start), nor does it explain when to use docker_exec vs docker_logs for interacting with a container. The context signals show many Docker-related siblings, making this gap more significant.
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 the full burden. It only states 'View logs', implying a read operation, but does not disclose behavioral traits like whether it blocks when follow=true, whether it requires a running container, or what happens if the container does not exist. This is a significant gap for a tool with no annotation safety hints.
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 short sentence, which is concise and front-loaded. However, it is under-specified for the tool's complexity; a slightly longer description could provide valuable context without sacrificing conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 3 parameters, no output schema, and no annotations, the description is incomplete. It does not explain the return format (e.g., lines of text), the effect of follow=true, or the behavior when lines exceeds available logs. For a moderately complex tool, more context is needed for an AI 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?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions (e.g., 'Number of lines to show'). It does not explain default behavior or edge cases, but the schema already documents the parameters adequately.
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 'View logs from a Docker container' uses a specific verb ('view') and resource ('logs from a Docker container'). It clearly distinguishes from sibling tools like docker_stats (system stats), docker_list (list containers), and docker_exec (execute commands), making it unambiguous what this tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives such as system_logs (for general system logs) or docker_exec (to retrieve logs via command). It does not mention prerequisites (e.g., container must be running) or when to avoid using it (e.g., if follow is true and may block).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries full burden. It only states the action without disclosing that restarting is a destructive operation (stops and starts the container, potentially losing in-memory state) or that the container must be running to succeed. No side effects or behavioral traits are mentioned.
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. However, it is slightly too terse, sacrificing necessary detail for brevity. A slightly longer description could improve clarity without losing conciseness.
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 annotations and output schema, the description should provide more context about the operation's effects (e.g., container will be stopped and started, potential downtime) and expected return values. The current description is insufficient for an agent to fully understand the tool's behavior.
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% (the 'container' parameter includes a description: 'Container name or ID'). The tool description adds no additional meaning beyond what the schema already provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Restart') and the resource ('a Docker container'), using a specific verb+resource pattern. This distinguishes it from sibling tools like docker_start (start a stopped container) and docker_stop (stop a running container).
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 docker_stop followed by docker_start, or what prerequisites exist (e.g., container must be running). The description lacks any context about usage scenarios or contraindications.
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. It correctly indicates a mutation (create), but does not disclose whether the operation is idempotent, what happens on duplicate titles, permission requirements, or rate limits. The basic description is accurate but incomplete for an AI agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, clear sentence that efficiently conveys the action. Every word serves a purpose with no fluff, and the structure is front-loaded with the core verb-resource action.
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 relative simplicity (4 parameters, no nested objects, no output schema) and high schema coverage, the description is adequate but minimal. It does not explain what the return value or success indicator is, but without an output schema, the agent might need additional guidance on response format.
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 baseline is 3. The description adds no parameter-specific information beyond what the schema already provides. For a tool with 4 parameters and 3 required, the description could usefully explain optional parameters like 'body' (e.g., Markdown supported) or implied defaults.
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 'Create a new issue in a repository' with a specific verb and resource. It distinguishes itself from sibling tools like gitea_issues (which likely lists issues) and gitea_repos, but could be slightly more explicit about scope (e.g., whether this works for any repository or only accessible ones).
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 gitea_issues (which might be for fetching/listing), or what prerequisites exist (e.g., authentication, repository existence). The description does not mention when not to use it or offer any context 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.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of disclosing behavioral traits like whether this is a read-only operation, what happens if the model doesn't exist, or if it requires network access. The description only states it 'gets information,' offering no depth on side effects, errors, or performance.
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 uses a single clear sentence that is front-loaded with the action and resource. While concise, it could benefit from additional context without sacrificing brevity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a single parameter, no output schema, and no annotations, the description is minimal. It doesn't specify the nature of the 'detailed information' returned, error handling, or prerequisites (e.g., model must be pulled), leaving the agent to assume a capable implementation may not exist.
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%, meaning the schema already documents the 'model' parameter as 'Model name.' The description adds no further semantics beyond what the schema provides, so baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('detailed information about a specific model'), clearly distinguishing it from siblings like ollama_list (which lists all models) or ollama_status (which checks overall Ollama health). However, it doesn't specify what kind of information (e.g., architecture, parameters, quantization), 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this should be used instead of ollama_list when a user needs details on a single model, but it provides no explicit guidance on when not to use it, prerequisites (e.g., model must exist), or alternatives among siblings.
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?
Since no annotations are provided, the description carries the full burden of behavioral disclosure. The description only says 'Read contents', which implies a safe, non-destructive operation, but it does not disclose what happens if the file does not exist (error?), whether it follows symlinks, or if there is a size limit. The lack of annotations amplifies the need for more detail here.
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 short sentence that is easy to parse and front-loaded with the key verb. It is concise but arguably too brief given the lack of annotations. It earns a 4 because it is efficient, though it could include a bit more context without becoming verbose.
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 (single parameter, no output schema, no nested objects), the description is nearly complete for basic usage. However, it lacks information about file types supported, error cases, or behavioral details that would be needed for robust agent decision-making. A 3 reflects that it is adequate for a simple tool but missing important context.
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 100% coverage with a single required 'path' parameter, and its description ('File path relative to workspace root') is already clear. The tool description adds no new semantic information beyond what the schema provides. However, with only one parameter and high schema coverage, the description's minimal addition is acceptable, earning a 4 as per the scoring rule (baseline 3, with high coverage and single param, slight bonus for clarity).
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 uses the verb 'Read' with the resource 'contents of a file in the workspace', which is specific and distinguishable from sibling tools like workspace_list, workspace_tree, workspace_write, and workspace_search. It lacks explicit mention of the path parameter's role, but the verb+resource pairing is strong.
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 vs alternatives. For example, it does not clarify whether this tool is for textual files only, or if it works on binary files. No exclusions or when-not-to-use conditions are provided, leaving the agent to infer usage from context signals 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 full burden for behavioral disclosure. It states the tool checks installation and working state but does not reveal what constitutes 'working,' what output to expect, whether it's idempotent, or if it requires network access. The description leaves 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.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single efficient sentence that clearly conveys the tool's purpose with no wasted words. It is front-loaded and 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 the tool has no parameters, no output schema, and no annotations, the description is adequate for a simple no-argument check but could be more complete. It doesn't specify return values or error conditions, which would help the agent understand what 'working' means in practice. For a tool of minimal complexity, it's barely sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema description coverage is 100%, so there are no parameter semantics to document. The description is appropriately minimal as no parameters exist. Baseline for 0 parameters is 4, as there is no gap in parameter understanding.
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 it checks if Claude Code CLI is installed and working, specifying both the target (Claude Code CLI) and the action (check install and working state). While it distinguishes from siblings like claude_ask, claude_task, etc. by focusing on installation status rather than functionality, it could be more specific about what 'working' means.
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 ollama_status or system_status for health checks of other services. There is no explicit discussion of when to use it, when not to use it, or prerequisites.
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 fully disclose behavior. The description is minimal and does not explain that git commands are executed directly and may modify the repository (e.g., commit, push), or that this could have side effects. However, the verb 'run' implies execution, and the examples given (status, log, diff) are read-only, partially mitigating the concern. A 3 is appropriate because the description does not contradict any annotation but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise at one sentence. It front-loads the action and resource. While it earns its place by stating the purpose, it could benefit from one more sentence clarifying scope or behavior without becoming verbose.
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 complexity of running arbitrary git commands (potential for mutation, security implications, output handling) and the lack of annotations or output schema, the description is somewhat incomplete. It does not explain what happens to the output, error handling, or working directory assumptions. However, for a common operation like 'run git command', many agents may infer these details. A 3 reflects adequate but not thorough coverage.
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 high (100%), so the baseline is 3. The description does not add any parameter-level guidance beyond what the schema provides. For command, it gives examples (status, log, diff) but does not clarify if arbitrary git commands are allowed, if there are restrictions, or if output is captured. The description adds minimal value over the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Run git commands in a project directory'. It specifies the verb 'run' and the resource 'git commands in a project directory'. While it distinguishes itself from sibling non-git tools, it does not differentiate from other git-related siblings like gitea_repos, gitea_repo_info, etc., which operate on a remote Gitea service versus local repositories.
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. For example, it doesn't mention that this is for local repository operations while gitea_* tools are for remote Gitea API interactions. There is no mention of prerequisites (e.g., directory must be a git repository), no exclusions, and no alternatives.
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 the full burden of behavioral disclosure. It states it lists projects (a read operation), but does not reveal any side effects, performance expectations, or limitations (e.g., whether hidden files are included, if the list is recursive). For a tool with no annotations, this is insufficient.
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, concise, and front-loaded with the verb and resource. There is no extraneous information. Every word 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 the lack of output schema and annotations, the description is minimal. It tells the agent what the tool does but not what the output looks like (e.g., is it a list of strings, objects with paths?). For a simple list tool this may be adequate, but additional context about return format or behavior on empty directories would improve completeness.
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?
There are zero parameters, and schema coverage is 100% (trivially). The description does not need to add parameter semantics since none exist. It correctly implies the tool is a simple list with no filters, which aligns with the empty schema.
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 uses a verb 'list' and resource 'projects', specifying the location 'workspace directory'. It distinguishes itself from siblings like workspace_tree (which likely lists directory structure) and workspace_search (which searches files). However, 'projects' is somewhat ambiguous—it could refer to folders or a specific project concept—so it's not a perfect 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 use cases, prerequisites, or scenarios where another tool (e.g., workspace_tree or workspace_search) would be more appropriate. The agent is left to infer usage from 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 behavioral disclosure. It does not state whether the tool is read-only (likely it is, but not confirmed), what the output format is (e.g., plain text, structured), or any potential side effects. The description is too brief to provide sufficient transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, front-loaded sentence with no unnecessary words. It efficiently conveys the core action. Every word is meaningful, and it avoids redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple explanation tool, the description is somewhat adequate but lacks completeness. It does not mention what sort of explanation the agent can expect (e.g., code logic, architecture, usage), nor does it address output format or length. Given no output schema, the description should clarify the return value. It is minimally 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 baseline is 3. The description adds minor context ('Ask Claude Code to explain how specific code or a feature works'), reinforcing the purpose but not adding detailed semantics beyond what the schema already provides for target and project. No additional parameter constraints or examples are given.
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 explains 'how specific code or a feature works', using a specific verb ('explain') and resource ('code/feature'). This distinguishes it from sibling tools like claude_ask (general questions), claude_task (execution), or claude_review (code review).
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 usage guidelines are provided. The description does not specify when to use this tool versus alternatives, nor does it mention any prerequisites, limitations, or when not to use it. An agent would have no explicit guidance on selecting this tool over similar sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It only states that Claude will modify files directly, which is a key behavioral disclosure. However, it does not mention safety, reversibility, permissions, whether the tool is destructive, or what happens to existing changes. Given the lack of annotations, this is insufficient.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence that is concise and gets the point across. It front-loads the core action ('Give Claude Code a task to complete') and includes examples. However, it could be slightly more structured to improve scannability.
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 3 parameters (2 required) and no output schema. The description does not explain return values, whether the task is synchronous or asynchronous, or if additional confirmation or output is expected. Key behavioral details are missing, making the description incomplete for a file-modifying tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description adds no additional meaning beyond the schema's parameter descriptions. Each parameter is documented in the schema, and the tool description does not elaborate on their usage or constraints.
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: giving a task to Claude Code to complete, with specific examples (write code, refactor, fix bug). It also notes that Claude modifies files directly, which distinguishes it from sibling tools like claude_ask (for questions) or claude_review (for reviewing).
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 code modification tasks through examples, but it does not explicitly state when to use this tool versus alternatives like claude_ask, claude_review, or claude_explain. No explicit context or exclusion criteria are provided.
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 states 'Show resource usage statistics', implying a read-only operation, but lacks details on what statistics (CPU, memory, network, etc.), whether it's real-time or a snapshot, or requirements like running containers. The description is too shallow for a tool with 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.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single short sentence, front-loaded and without fluff. However, it could benefit from a slightly more structured explanation (e.g., listing typical stats shown) without becoming verbose, so it's not a perfect 5.
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 no output schema and no annotations, the description should provide more context about the return format, types of statistics, and any operational constraints (e.g., requires running containers). It falls short of being complete for an agent to fully understand usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty with 100% coverage. According to guidelines, baseline is 4 for no parameters. The description does not need to add parameter info, and it does not conflict.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Show' and a clear resource 'resource usage statistics for containers'. It clearly distinguishes from sibling tools like docker_list (lists containers) and docker_logs (shows logs).
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 on when to use docker_stats versus alternatives, no prerequisites mentioned (e.g., containers must be running), nor when not to use it. Implied context from the tool name and description is minimal.
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 bears the full burden. The description states it 'reviews code and provides feedback', which implies a read-only, non-destructive behavior. However, it does not disclose whether the review triggers any side effects (e.g., file writes, git commits), or confirm that it is safe to use. Given the lack of annotations, more explicit behavioral disclosure would be beneficial.
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 very concise with a single sentence: 'Ask Claude Code to review code and provide feedback.' It is front-loaded and to the point. While it could be more specific about scope (e.g., 'in the specified project'), it does not waste words. It could be slightly longer to include usage guidance without becoming bloated.
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 context (3 parameters, 100% schema coverage, no output schema, no annotations, sibling tools), the description is adequate but could be more complete. It does not mention the return format or whether feedback is provided in the response or asynchronously. For a tool that may produce lengthy output, some guidance on what to expect would help the agent evaluate success. The description also misses the opportunity to clarify the relationship with similar claude_* tools.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the baseline is 3. The description does not add any additional semantics beyond what the input schema already provides. Each parameter (files, focus, project) is well-described in the schema, and the description does not need to add further value since schema coverage is complete. No points added or deducted.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: to ask Claude Code to review code and provide feedback. The verb 'review' combined with 'code' and 'provide feedback' clearly conveys the action, and the input schema's focus parameter distinguishes this from other claude_* tools that might involve asking questions or explaining.
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 does not explicitly state when to use this tool versus alternatives. However, the tool's name (claude_review) and the availability of sibling tools like claude_ask, claude_task, and claude_explain provide implicit context. The description could be improved by noting when a code review is appropriate compared to general Q&A or task execution.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided (no readOnlyHint, destructiveHint, etc.), the description carries the full burden. It states the tool 'lists' containers, implying a read-only operation, which is consistent. The description doesn't add any additional behavioral context such as whether it can be slow with many containers, whether it requires Docker daemon access, or any side effects. It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no filler or redundant words. Every word is meaningful and immediately communicates the tool's purpose. It is appropriately front-loaded and sized perfectly for a simple list tool.
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 low complexity of the tool (one boolean parameter, no output schema, no nested objects), the description is nearly complete. However, it could mention that the result lists container IDs, names, states, or other details to set expectations. Since there is no output schema, a brief note on the return fields would improve completeness. The 100% schema coverage partially compensates.
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 a single parameter (all). The description doesn't detail the 'all' parameter, but the schema already provides a clear description ('Show all containers (including stopped). Default: true'). Since the schema covers the parameter well, the description doesn't need to repeat it. The description adds no extra meaning, but given high schema coverage, baseline is 3, and it earns a 4 because it's clean and doesn't introduce confusion.
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 clear verb-resource structure ('List all Docker containers'), which distinguishes it from sibling tools like docker_start, docker_stop, etc. However, it doesn't explicitly state that this is limited to containers and not images or other Docker resources, though the name implies it. The purpose is clear but lacks a small degree of specificity about scope.
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 like docker_stats, docker_logs, or docker_images. Given the sibling tools cover many Docker operations, there is no explicit when-to-use or when-not-to-use guidance, leaving the agent to infer usage solely from the tool name and 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?
No annotations are provided, so the description must disclose behavioral traits. It only states 'List running processes', with no mention of permissions, read-only nature, error scenarios, or output behavior. This is minimal disclosure for a tool that likely requires system access.
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?
A single sentence contains the essential information with no waste. It is front-loaded and concise. However, it is slightly too brief and could incorporate a bit more context without becoming verbose.
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 simplicity of the tool (no output schema, 2 optional parameters, no annotations), the description covers the basic purpose but lacks details on default limit, output format, or potential limitations. It is minimally complete for a straightforward listing 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?
The input schema provides descriptions for both parameters (limit, filter) with 100% coverage. The description adds only a redundant mention of filtering by name, offering no additional meaning beyond the schema. Baseline 3 is appropriate since schema covers the parameters adequately.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('List') and resource ('running processes'), clearly indicating the tool's functionality. It also includes the optional filter capability, which distinguishes it from sibling tools like system_uptime or system_status that handle different system information.
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 does not explicitly state when to use this tool versus alternatives (e.g., docker_stats for container processes). However, the purpose is straightforward and the sibling tools are sufficiently distinct, allowing an implicit usage inference. Some guidance on exclusions would improve clarity.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behaviors. It only states the base action without revealing whether the file is overwritten, whether directories are created, permission requirements, or error handling. This is a significant gap for a mutation 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?
A single, focused sentence with no redundancy. It is appropriately concise for the tool's simple purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no annotations and no output schema, the description must explain behavioral details and expected returns, but it does not. Missing overwrite semantics, side effects, and error handling leaves the tool under-specified.
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 provides 100% coverage with clear descriptions for both path and content, so the description adds no extra meaning but also does not need to. 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 'Write content to a file in the workspace' clearly specifies the action (write) and resource (file in workspace), distinguishing it from sibling tools like workspace_read and workspace_list.
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 through the verb 'write' but provides no explicit guidance on when to use this tool versus alternatives, nor any prerequisites or exclusions. The context is clear enough for basic use but lacks explicit direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully convey behavioral traits. It only states 'List branches in a repository', implying a read operation, but omits details like authentication requirements, pagination, error handling, or what happens if the repo does not exist. This is insufficient for an agent to fully understand 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?
The description is a single sentence with zero wasted words. It is efficiently front-loaded and easy to parse.
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 (2 string params, no output schema, low complexity), the description covers the basic purpose. However, it lacks details about return format, sorting, or boundary conditions (e.g., empty repository), leaving some gaps for an agent.
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 both parameters with plain descriptions ('Repository name', 'Repository owner'), achieving 100% schema coverage. The description adds no further semantic information (e.g., format, constraints, or context). Baseline 3 applies per guidelines.
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 'List branches in a repository' uses a specific verb ('List') and resource ('branches in a repository'), clearly distinguishing it from sibling tools like gitea_repos (lists repositories) and gitea_issues (lists issues).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit when-to-use or when-not-to-use guidance is provided. The sibling context makes the purpose obvious, but the description does not mention alternatives or prerequisites, leaving the agent to infer usage from 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 provided, the description carries full burden for behavioral disclosure. It only states 'List all available models' without indicating whether this is a read-only operation, whether it requires network access, or any potential side effects. Minimal transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 5 words with no extraneous information. It is front-loaded and to the point.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no parameters and no output schema, the description is minimally adequate. However, it lacks details about what the list contains (e.g., model names, sizes, status) and does not clarify if 'available' means locally cached or from a remote repository. Adds no context beyond the name.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100% (empty schema). Per guidelines, baseline is 4 because there are no parameters for the description to explain. The description does not need to add parameter details.
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 'List all available Ollama models' uses a specific verb ('List') and resource ('Ollama models'), clearly distinguishing from sibling tools like ollama_run, ollama_pull, and ollama_delete which perform different 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?
No guidance is provided on when to use this tool versus alternatives like ollama_status or when not to use it. The description does not mention any prerequisites, filtering, or exclusion criteria.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It correctly identifies the action as downloading, implying a network operation, but does not disclose potential side effects, such as disk usage or time consumption. The description is accurate but lacks detail about behaviors like installation process, cache management, or progress feedback. There is no contradiction with annotations as none exist.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that directly states the tool's purpose with no extraneous information. It is front-loaded and efficient, earning its place without any wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, no output schema, no nested objects), the description is adequate but minimal. It tells the agent what the tool does but does not explain return values (which models are pulled, success/failure indications) or constraints (e.g., requires network, model naming conventions beyond the example). For a simple tool, it covers basic functionality but lacks completeness in behavioral expectations.
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 100% description coverage, already documenting the only parameter with an example ('llama3.2, codellama'). The description adds no further param value but neither is needed; the schema fully covers it. The tool has a single parameter, so baseline is high. The example in the schema provides useful context beyond a mere name.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Download/pull') and the resource ('a new model from Ollama registry'). It effectively communicates the core purpose of the tool, which is to retrieve a model. While it lacks specific differentiation from sibling tools like ollama_list or ollama_info, the verb 'pull' indicates downloading a model compared to listing or showing info, though it could be more explicit.
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 downloading models, which is clear from the context. However, it provides no guidance on when to use this tool versus alternatives, such as when a model is not available locally (vs ollama_list) or when running a model (vs ollama_run). It does not set expectations about prerequisites, like internet connectivity, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. The description states it retrieves system data, which implies no destructive side effects. However, it does not mention typical behavioral details such as return format, data freshness, or whether it accesses remote systems. It avoids contradicting any annotations (none exist) but adds limited behavioral nuance.
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 6 words, which is concise. It front-loads the action and resource effectively. However, it could be slightly more descriptive without becoming verbose—e.g., mentioning the return type—but it remains efficient and focused.
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 zero parameters and no output schema, the description adequately covers the tool's purpose. For a simple read-only command, the description is complete enough to allow correct agent selection. It could mention the expected output format, but that's not critical for selection among siblings.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and schema description coverage is 100% (all properties are covered implicitly). Since there are no parameters to document, the description doesn't need to add meaning beyond the schema. A score of 4 reflects that the schema is complete and no parameter information is missing.
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 specifies the verb 'get' and the resources 'system uptime and load average'. It distinguishes from siblings like system_status and system_processes by focusing on the specific metric of uptime and load average, not general status or process lists.
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 this is for querying system-level metrics related to uptime and load average. However, it does not explicitly state when to use this versus alternatives like system_status (which may also provide load info) or when not to use it. It provides basic context but no exclusions or alternative tool guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It correctly states the tool shows a tree structure but does not disclose default behavior (e.g., starts from workspace root), error handling for invalid paths, or whether hidden files are included. The schema provides some detail on parameters (depth default 3), but the description itself adds minimal behavioral context beyond the literal purpose.
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 of nine words, containing zero filler or redundancy. Every word is meaningful and directly conveys the tool's function. It is optimally concise for its purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (two optional parameters, no output schema), the description is largely sufficient. It captures the core function. However, it could be slightly more complete by clarifying that the output is a textual tree representation (e.g., 'returns a formatted tree') or that it is a read-only operation, but these are not critical gaps.
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% (both 'path' and 'depth' are described in the input schema). The description does not add any further semantics or usage hints for these parameters beyond what the schema already 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 'Show directory tree structure of a project' uses a specific verb ('Show') and clearly identifies the resource ('directory tree structure of a project'). It distinguishes well from sibling tools like workspace_list (flat listing) and workspace_read (file content), making the tool's purpose immediately obvious.
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 (e.g., 'for visualizing project hierarchy'), prerequisites, or when not to use it. Given siblings like workspace_list and workspace_search, explicit usage context would help an AI agent decide correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It is a read-only, non-destructive check, but the description doesn't state this explicitly. It also does not mention what happens if Ollama is not installed (error vs. status false). With no annotations, a brief mention of the return behavior or safety 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 a single, complete sentence that is front-loaded with the key action and resource. Every word is necessary, and there is no superfluous text. It is appropriately concise for a simple, parameterless tool.
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 status check with no parameters and no output schema, the description is nearly complete. It states the core purpose. However, it could be slightly more complete by noting that it checks the local service (since Ollama could be remote) or indicating the type of result (boolean vs. status string). Given the low complexity, this is a minor gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has no parameters (0), and schema description coverage is 100% (trivially). The description does not need to add param meaning because there are none. It correctly omits any param-related text, meeting the baseline.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Check') and the target resource ('Ollama service'). It also uses a specific verb-resource combination that is distinct from siblings like 'ollama_list' or 'system_status'. However, it could additionally clarify that it checks local availability, not a remote service.
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 when needing to verify Ollama service status before other operations, but it doesn't explicitly state when to use this over 'system_status' or 'claude_status'. No exclusions or alternatives are mentioned. With many sibling tools, more explicit guidance would help.
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 provided, the description carries full burden for behavioral disclosure. It conveys a read-only, immediate check operation which is appropriate, but lacks details about side effects, units of measurement, or refresh behavior. It is adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence that conveys the purpose and scope without any wasted words. It is front-loaded and perfectly sized for a parameterless tool.
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 zero parameters, no output schema, and no annotations, the description is nearly complete for this simple read-only tool. It describes the input (none) and the high-level output scope well. A minor gap is not specifying whether the output format is raw metrics or human-readable, but this does not critically impair an agent's ability to use 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?
Schema description coverage is 100% because there are zero parameters, so the schema already fully documents the interface. The description adds value by explaining what data the agent will receive, which is a bonus beyond the empty schema.
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 a specific verb ('Get') and resource ('current system status') along with the data components covered ('CPU, RAM, and Disk usage'). It distinguishes itself from sibling tools like system_uptime, docker_stats, and system_processes which cover more narrow or different aspects of system monitoring.
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 this is a general health check tool, which fits with no parameters and siblings covering sub-topics. However, there is no explicit guidance on when to use this versus more specific tools like system_uptime or system_processes, nor when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
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MCP Security
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Prompt Injection
WebAssembly

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