Chisel Knowledge MCP

by teknologika

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose with no overlap: ingest tools handle different input sources (clipboard, text, URL), list tools target different directories (inbox, knowledge, workspaces), and read/write/search/archive/status tools perform unique operations. An agent can easily differentiate them based on their specific actions and targets.
Naming Consistency5/5
All tools follow a consistent 'knowledge_verb_noun' pattern (e.g., knowledge_ingest_url, knowledge_list_inbox, knowledge_search). This uniform naming convention makes the tool set predictable and easy to navigate, with no deviations in style or structure.
Tool Count5/5
With 11 tools, the server is well-scoped for knowledge management, covering ingestion, organization, querying, and maintenance. Each tool earns its place by addressing a specific need in the workflow, from input handling to file management and search, without being overly sparse or bloated.
Completeness5/5
The tool set provides complete coverage for knowledge management: ingestion from multiple sources (clipboard, text, URL), listing and reading files, searching content, writing compiled articles, archiving processed items, and workspace inspection. There are no obvious gaps, enabling agents to handle the full lifecycle of knowledge processing.
Average 2.7/5 across 11 of 11 tools scored. Lowest: 2.1/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
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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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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. 'Inspect' implies a read operation, but it doesn't disclose behavioral traits such as whether it requires permissions, what data it returns, or if it has side effects. The description is too vague to inform the agent adequately.
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 with zero waste. It is appropriately sized and front-loaded, though its brevity contributes to under-specification rather than clarity.
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 annotations, no output schema, and low schema coverage, the description is incomplete. For a tool with one parameter and siblings that suggest complex knowledge management, it lacks details on behavior, return values, and differentiation, leaving significant gaps for the agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, with one parameter 'workspace' undocumented in the schema. The description adds no meaning beyond the schema, failing to explain what 'workspace' represents (e.g., an ID, name, or path) or its format. It does not compensate for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose2/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Inspect a workspace' restates the tool name 'knowledge_workspace_status' with minimal elaboration, making it tautological. It specifies the verb 'inspect' and resource 'workspace' but lacks detail on what inspection entails or what distinguishes it from siblings like 'knowledge_list_workspaces' or 'knowledge_read'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines1/5
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. With siblings like 'knowledge_list_workspaces' (likely listing workspaces) and 'knowledge_read' (likely reading content), the description offers no context on usage scenarios, prerequisites, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions reading a file but doesn't disclose behavioral traits like permission requirements, error handling (e.g., if the file doesn't exist), or output format (e.g., text content). This leaves significant gaps in understanding how the tool behaves.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero waste—it directly states the tool's action and resource. It's appropriately sized and front-loaded, making it efficient for quick understanding.
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 complexity (a read operation with 2 parameters), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't cover key aspects like what 'read' entails (e.g., returns file content), error cases, or how it differs from siblings, leaving the agent under-informed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so parameters 'workspace' and 'path' are undocumented. The description adds no meaning beyond the schema—it doesn't explain what a 'workspace' or 'path' represents, their formats, or examples. This fails to compensate for the low schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the action ('Read') and resource ('a knowledge file from a workspace'), which clarifies the tool's basic function. However, it doesn't differentiate from siblings like 'knowledge_search' or 'knowledge_list', which might also involve reading knowledge files, making the purpose somewhat vague in context.
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 'knowledge_search' or 'knowledge_list'. It lacks explicit context, prerequisites, or exclusions, leaving the agent with minimal direction for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('search') but doesn't describe what 'search' entails—whether it's full-text, keyword-based, returns snippets or full content, has pagination, requires specific permissions, or has rate limits. For a search tool with zero annotation coverage, this leaves critical behavioral traits unspecified.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at three words, with no wasted language. It's front-loaded with the core action ('search'), making it easy to parse quickly. Every word earns its place by specifying the action and target, though this brevity comes at the cost of detail.
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 complexity (a search operation with 3 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the search returns (e.g., results format), how it behaves (e.g., ranking, filtering), or prerequisites (e.g., workspace access). For a search tool in a knowledge system with many siblings, more context is needed to use it effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning parameters 'workspace', 'query', and 'limit' have no documentation in the schema. The description doesn't add any parameter semantics—it doesn't explain what 'workspace' refers to (e.g., a workspace ID or name), what 'query' should contain (e.g., search terms), or how 'limit' affects results. This fails to compensate for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Search workspace knowledge' clearly states the verb ('search') and resource ('workspace knowledge'), making the purpose understandable. However, it doesn't differentiate from sibling tools like 'knowledge_list' or 'knowledge_read' that might also retrieve knowledge, leaving ambiguity about what makes this specific search operation unique.
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. With siblings like 'knowledge_list' (likely listing knowledge items), 'knowledge_read' (likely reading specific items), and 'knowledge_archive' (likely archiving), there's no indication of when search is preferred over these other retrieval methods, leaving the agent to guess based on tool names 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?
No annotations are provided, so the description carries full burden. It implies a destructive/mutative action ('Move') but doesn't disclose behavioral traits like permissions needed, whether the move is reversible, error conditions, or what happens to the original file location. The description adds minimal context beyond the basic action.
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 with zero waste. It's appropriately sized and front-loaded with the core action, making it easy to parse quickly.
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 annotations, 0% schema coverage, no output schema, and a mutation tool with 2 parameters, the description is incomplete. It lacks details on behavior, parameters, error handling, and output, leaving significant gaps for an agent to use it correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'file' but not 'workspace', and provides no details on parameter formats, constraints, or examples (e.g., file paths, workspace identifiers). The description adds limited meaning beyond 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 action ('Move') and the resource ('a processed inbox file'), specifying the destination ('to inbox/archived/'). It distinguishes from siblings like knowledge_list_inbox (list) and knowledge_read (read), but doesn't explicitly contrast with other write/move operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., file must be 'processed'), exclusions, or comparisons to siblings like knowledge_write or other knowledge_* 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?
With no annotations provided, the description carries full burden but lacks critical behavioral details. It mentions reading and writing but doesn't disclose permissions needed, whether this is a mutation (implied by 'write'), error handling (e.g., if clipboard is empty), or rate limits. The description adds minimal context beyond the basic action.
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 with zero waste. It's front-loaded with the core purpose and appropriately sized for the tool's complexity, making it easy to parse quickly.
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 annotations, no output schema, and 0% schema coverage, the description is incomplete. It covers the basic action but misses critical context: parameter semantics, behavioral traits (e.g., mutation effects, error cases), and output details. For a tool with 2 parameters and implied mutation, this is inadequate.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate but provides no parameter information. It doesn't explain what 'workspace' or 'title' represent, their formats, or how they affect the operation. This leaves both parameters undocumented, failing to add meaning beyond the bare 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 action ('Read clipboard text and write it into a workspace inbox') with specific verbs and resources. It distinguishes this tool from siblings like knowledge_ingest_text or knowledge_ingest_url by specifying the clipboard as the source, but doesn't explicitly differentiate from all siblings like knowledge_write.
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. It doesn't mention prerequisites (e.g., clipboard access), when-not-to-use scenarios, or compare it to siblings like knowledge_ingest_text for direct text input or knowledge_write for general writing.
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. 'Write' implies a mutation operation, but the description doesn't specify whether this requires authentication, what happens if the workspace doesn't exist, whether the operation is idempotent, or what the response format looks like. It provides minimal behavioral context beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just 6 words, front-loading the essential action and target. Every word earns its place with no redundancy or unnecessary elaboration, making it efficient for quick comprehension.
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 mutation tool with 3 parameters, 0% schema coverage, no annotations, and no output schema, the description is inadequate. It doesn't explain what happens after ingestion, how to verify success, error conditions, or how this tool relates to other knowledge tools. The minimal description leaves too many operational questions unanswered.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage and 3 parameters (workspace, content, title), the description provides no information about parameter meanings. It doesn't explain what constitutes a valid workspace identifier, what format/content restrictions apply to the text, or whether the title parameter is optional/required. The description fails to compensate for the complete lack of schema documentation.
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 ('Write raw text') and target ('into a workspace inbox'), providing a specific verb+resource combination. However, it doesn't distinguish this tool from sibling tools like 'knowledge_ingest_clipboard' or 'knowledge_ingest_url' which likely perform similar ingestion functions with different input sources.
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. With multiple sibling ingestion tools (knowledge_ingest_clipboard, knowledge_ingest_url), there's no indication of when raw text ingestion is preferred over clipboard or URL ingestion, nor any mention of prerequisites or constraints.
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. 'Ingest' implies a write/mutation operation, but the description doesn't clarify what 'ingest' entails (e.g., fetching content, storing metadata, processing), whether it's idempotent, what permissions are needed, or what happens on success/failure. This leaves significant behavioral gaps.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is perfectly concise at 6 words, front-loading the core purpose with zero wasted words. Every element ('ingest', 'URL', 'workspace inbox') earns its place in communicating the essential function.
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 mutation tool with 3 parameters (0% schema coverage), no annotations, and no output schema, the description is inadequate. It doesn't explain what 'ingest' means operationally, what the parameters represent, what happens after ingestion, or how this differs from other ingestion methods. More context is needed for effective tool selection and use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage for all 3 parameters, the description adds no parameter semantics beyond what's implied by the tool name. It doesn't explain what 'workspace' refers to, what format 'url' should have, or whether 'title' is required/optional. The description fails to compensate for the complete lack of schema documentation.
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 ('ingest') and target resource ('a URL into a workspace inbox'), making the purpose immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'knowledge_ingest_text' or 'knowledge_ingest_clipboard', which would require mentioning the specific URL ingestion capability.
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. With multiple ingestion tools (URL, text, clipboard) and other knowledge management tools available, there's no indication of prerequisites, typical use cases, or distinctions from 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?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool lists files but doesn't mention whether this is a read-only operation, what permissions are required, how results are formatted (e.g., pagination, sorting), or error conditions. This leaves significant gaps for an agent to 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, efficient sentence that directly states the tool's purpose without unnecessary words. It's front-loaded with the core action and resource, making it easy to parse quickly.
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 is incomplete for a tool with 2 parameters. It doesn't cover behavioral aspects like safety, permissions, or result format, and with 0% schema coverage, parameter details are insufficient. For a list operation in a knowledge system, more context is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'workspace' and 'directory' implicitly but doesn't explain their semantics (e.g., what constitutes a valid workspace, whether directory is optional or has defaults). With 2 parameters and no schema descriptions, this adds minimal value beyond the parameter names.
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 target resource ('markdown files in a workspace knowledge directory'), which is specific and unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'knowledge_list_inbox' or 'knowledge_list_workspaces', which also list knowledge items but in different contexts.
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. With siblings like 'knowledge_list_inbox', 'knowledge_list_workspaces', and 'knowledge_search' available, there's no indication of context, prerequisites, or exclusions to help an agent choose appropriately.
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 'Write' implies a mutation operation but doesn't clarify permissions, whether it overwrites existing files, error handling, or any side effects. This is inadequate for a write tool with zero annotation coverage.
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 directly states the tool's purpose without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 complexity of a write operation with 3 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavior, parameter usage, and expected outcomes, making it insufficient for safe and effective tool invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, meaning none of the three parameters (workspace, path, content) are documented in the schema. The description mentions 'workspace' and 'path' implicitly but adds no details on their formats, constraints, or meanings, failing to compensate for the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Write') and the target resource ('compiled article into the workspace knowledge directory'), making the purpose understandable. However, it doesn't explicitly differentiate this tool from siblings like knowledge_ingest_text or knowledge_archive, which might also involve writing content, so it misses full sibling 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. With siblings like knowledge_ingest_text and knowledge_archive available, there's no indication of specific contexts, prerequisites, or exclusions for using knowledge_write, leaving the agent without usage 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool lists files but doesn't describe any behavioral traits such as permissions needed, rate limits, pagination, or what 'uncompiled' means operationally. This leaves significant gaps in understanding how the tool behaves beyond its basic function.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with no wasted words, making it highly concise and front-loaded. Every part of the sentence contributes directly to the tool's purpose, earning its place efficiently.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of listing files (which may involve permissions, filtering, or output details), no annotations, no output schema, and low schema coverage, the description is incomplete. It doesn't address key aspects like return format, error handling, or how 'uncompiled' is defined, leaving the agent with insufficient context for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description implies a 'workspace' parameter by context ('in a workspace inbox'), but with 0% schema description coverage and 1 parameter, it doesn't add detailed meaning beyond what the schema minimally provides (e.g., format or examples for 'workspace'). The baseline is 3 since the schema covers the parameter structure, but the description offers limited compensation.
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 ('uncompiled files in a workspace inbox'), making the purpose understandable. However, it doesn't explicitly differentiate from siblings like 'knowledge_list' or 'knowledge_list_workspaces', which might also list items, so it's not fully specific to sibling context.
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 'knowledge_list' or 'knowledge_search'. It lacks any mention of prerequisites, exclusions, or comparative context, leaving the agent with minimal usage 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 carries full burden. It states this is a list operation but doesn't disclose behavioral traits like whether it returns all workspaces or paginated results, what format the output takes, or any authentication requirements. The description is minimal and lacks necessary operational context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, clear sentence with zero wasted words. It's front-loaded with the core action and resource, making it immediately understandable without unnecessary elaboration.
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 annotations and no output schema, the description is insufficient for a tool that likely returns structured data about workspaces. It doesn't explain what 'configured workspaces' means, what information is returned, or how the results are formatted. For a list operation with potential complexity, more context is needed.
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 description coverage, the baseline is 4. The description doesn't need to explain parameters since none exist, and it correctly indicates this is a simple listing operation without filtering or input requirements.
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 ('List') and resource ('configured workspaces'), making the purpose immediately understandable. It doesn't specifically differentiate from sibling tools like 'knowledge_list' or 'knowledge_list_inbox', but the resource specificity ('workspaces') provides some 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 guidance is provided about when to use this tool versus alternatives like 'knowledge_list' or 'knowledge_workspace_status'. The description simply states what it does without context about appropriate 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.

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