ideahub_mcp

by CobraChickenAI

Overview Schema Related Servers Score Discussions

Python

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Server Quality Checklist

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Latest release: v0.4.0
Disambiguation5/5
Each tool has a clearly distinct purpose: capture for new ideas, checkpoint for temporary traces, annotate for notes, promote for upgrading checkpoints, get/list/search/dump for retrieval, link for relationships, archive for soft deletion, and ping/recognize for admin. No two tools overlap in their core function.
Naming Consistency4/5
Tool names are all lowercase single words, mostly verbs (capture, archive, promote, etc.) with a few nouns (list, search, related). The pattern is simple and predictable, though not strictly verb_noun. Slight inconsistency exists between 'get' (noun) and 'capture' (verb), but it's minor.
Tool Count5/5
13 tools cover the full lifecycle of idea management: creation (capture, checkpoint), retrieval (get, list, search, dump, related, recognize), modification (annotate, promote, link), deletion (archive), and health (ping). The count is well-scoped for the domain.
Completeness3/5
The tool set covers creation, retrieval, linking, and soft archiving, but lacks a dedicated update tool for modifying an idea's core content. Annotations and promotions can indirectly update, but there's no way to edit the original content. This gap may cause agent failures when content needs correction.
Average 4.2/5 across 13 of 13 tools scored. Lowest: 3.5/5.
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
- Last stable release on May 2, 2026
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds behavioral details beyond annotations: self-links rejected, canonicalization of 'related' type, and normalization of task_ref to lowercase kebab-case. No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is highly concise: three sentences cover purpose, kinds, constraints, and normalization. No superfluous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core behavior and constraints but omits error handling (e.g., self-links, duplicate links) and does not explain the output schema. Given the output schema exists, return values are not required, but side effects and edge cases are lacking.
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 zero schema description coverage, the description must compensate, but it only partially explains parameters. It details 'kind' and 'task_ref' but does not describe 'source_id' and 'target_id' beyond being IDs of ideas.
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 connects two ideas and enumerates the four kinds of relationships. It also includes canonicalization and self-link rejection. However, the sibling tool 'related' shares a name with one of the kinds, which may cause 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 gives contextual clues for when to use (when current work reveals a relationship) but does not explicitly mention when not to use or compare with alternative tools like the sibling 'related'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only, idempotent, and non-destructive. The description adds behavioral context beyond annotations, such as default exclusions of archived items and checkpoint rows, which is valuable for agent decision-making.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: first sentence lists filters and return fields, second explains key defaults. It is concise, front-loaded, and free of redundant information.
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 10 parameters, an output schema exists, and no nested objects, the description covers return fields and two defaults but omits details on parameter formatting and interaction. It is adequate but not comprehensive.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate but only lists parameter names without explaining semantics like date format, tag matching logic, or behavior when multiple filters combine. This leaves significant ambiguity despite naming parameters.
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 lists ideas with filters and specifies the return fields. It distinguishes from siblings by focusing on listing with filters, but does not explicitly differentiate from the 'search' sibling tool.
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 provides guidance on defaults (excluded archived and checkpoints) and how to include them via parameters. However, it lacks clear directions on when to use this tool versus alternatives like 'search' or 'get', and no explicit when-not-to-use advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description valuably supplements the annotations (already indicating safe read-only operation) by detailing default behaviors: newest-first ordering, inlining of latest note, exclusion of archived and checkpoint rows unless overridden. This goes beyond what annotations provide, though it could mention potential truncation under token budget.
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 concise at three sentences, front-loading the core purpose and usage. It avoids redundancy but could be slightly more structured (e.g., listing defaults separately).
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 8 parameters and the presence of an output schema, the description provides adequate context for orientation usage but fails to explain several parameters (scope, since, actor, originator, include_all_notes) and does not describe the return format or token budget behavior. This leaves the agent with incomplete guidance.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description must compensate. It explains the meaning of 'include_archived' and 'include_checkpoints' (default false, toggle behavior) and implicitly the 'limit_tokens' parameter via 'token budget'. However, other parameters like 'scope', 'since', 'actor', 'originator', and 'include_all_notes' are left unexplained, leaving gaps.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's verb ('Dump'), resource ('scoped corpus'), and outcome ('single text blob under a token budget'). It also explicitly ties it to orientation ('what does this repo/user think about?'), distinguishing it from sibling tools like search or list that are more query-oriented.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool ('for orientation'), its default ordering ('newest ideas first'), and default exclusions ('archived excluded', 'checkpoints excluded'). However, it does not specify when not to use it or suggest alternative tools for more targeted queries.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description adds details beyond annotations: preservation of links, notes, and provenance via 'kind=\'promotion\''. Annotations indicate destructiveHint=true, which is consistent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences plus a key note about one-way behavior. No unnecessary words; front-loaded with purpose.
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?
Covers purpose and outcome well but lacks parameter documentation. With output schema present, return values are covered, but missing input semantics reduces completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description provides no explanation of parameters like 'id', 'actor', or 'originator', leaving semantics unclear.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states 'Promote a checkpoint to a durable idea' with a specific verb and resource. Distinguishes from siblings by explaining the context and one-way nature.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use (load-bearing working-memory trace) and that promotion is one-way, providing clear context for the agent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare it as read-only and idempotent. Description adds the behavioral distinction between single record and full list, which is valuable context beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. Information is front-loaded and efficient.
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?
Adequately covers the tool's functionality for a simple single-parameter tool. Does not mention return format or pagination, but output schema likely addresses that. Slight gap in not specifying any limits on the list mode.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description fully compensates by explaining the id parameter's effect: passing it retrieves detail on one actor, omitting it lists all. This is clear and unambiguous.
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?
Clearly states the tool inspects the actor table, with a specific verb and resource. Distinguishes from siblings by naming 'actor table,' but does not explicitly contrast with tools like 'list' or 'get' that may also operate on actors.
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?
Provides clear instructions on how to use the id parameter (pass for detail, omit for list), but does not advise on when to prefer this tool over alternatives like 'search' or 'list' among siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, safe behavior. Description adds detailed scoring logic (tag overlap, shared originator, recency), scope limits, and exclusion rules, exceeding 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?
Three sentences, front-loaded with purpose, followed by relevant details. No redundant or unnecessary text.
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?
With annotations and output schema present, description covers purpose, filtering options, and scoring. Missing explicit mention of max parameter is minor; overall complete for tool complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but description explains id, cross_scope, include_archived, and include_checkpoints. However, max parameter is not mentioned; its default and effect are left to schema, partially compensating.
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?
Description clearly states 'Find ideas related to the given id' with specific verb and resource. It provides scoring criteria and exclusions, differentiating from general search, though does not explicitly name sibling tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Describes when to use parameters like cross_scope, include_archived, include_checkpoints, and default behaviors. Does not explicitly compare to alternatives but gives sufficient context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Description confirms idempotency (matching idempotentHint=True) and discloses writing a note and setting archived_at. Annotations show no readOnly or destructive hints, and description adds specific behavioral details beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with three key points: purpose, idempotency, exclusion behavior. No redundancy, front-loaded with action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers main effects and behavioral context. Output schema exists, so return values are handled. Could mention prerequisites or error conditions, but overall sufficient for a simple archival tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains 'reason' parameter via 'write kind=... note with reason' but does not address 'actor' or 'originator'. 'id' is implicit. Adds some value but leaves gaps.
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: 'Archive an idea' with specific side effects (sets archived_at, writes note). It also explains the consequence for default listings. This distinguishes it from siblings like 'annotate'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context: 'Archived ideas are excluded by default from list/search/dump.' This implies when to use archive (to hide ideas). However, no explicit alternatives or when-not-to-use are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=false (write operation) and non-destructive, non-idempotent. The description adds valuable context: the trace is 'lightweight', not final; it returns candidates; task_ref normalization to lowercase kebab-case; kind_label enum; candidates parameter behavior. No contradiction found.
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 two paragraphs, front-loaded with purpose, then usage conditions, then parameter details. It is reasonably concise, though could be slightly tighter. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With 8 params, 1 required, no schema descriptions, and an output schema (not visible), the description covers usage, key parameter behavior, and return values (annotate_candidates, related_candidates). It misses explanation for some optional params but overall is thorough enough for an agent to use 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 coverage is 0% (no parameter descriptions in schema). The description explains task_ref (normalization), kind_label (enum values), and candidates (default, max, meaning of 0). However, it does not cover content, scope, tags, originator, actor. Partial but helpful.
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: 'Write a lightweight working-memory trace during a task.' It uses specific verbs and resources, and distinguishes itself from the sibling 'capture' tool by specifying that 'capture' is for final standalone ideas.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit when-to-use scenarios (e.g., 'non-trivial synthesis mid-task', 'decision the session will depend on') and when-not-to-use ('Do not use for final, standalone ideas'). It also names an alternative tool ('capture'). This gives clear guidance for tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations are basic (readOnlyHint false, etc.). The description adds behavioral details such as task_ref normalization to lowercase kebab-case and semantic labels for kind. No contradictions. Some traits like mutation are implied but not explicitly stated.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences with a list of use cases. Each sentence adds value, no fluff, and the main action is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 6 parameters, 0% schema coverage, and an output schema, the description covers the tool's purpose, usage, and two key parameters. However, actor and originator are missing. Overall still informative enough for typical use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, so description must compensate. It explains kind (lists semantic types) and task_ref (grouping + normalization). But actor and originator are not explained, leaving gaps. id and content are self-explanatory from context.
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 ('Append a note') and resource ('existing idea'), and distinguishes when to use this tool vs. creating a separate idea. It clearly states the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states when to use: when current work updates an existing idea, to attach new evidence/correction, and when not to create a separate idea. Also implies alternatives (e.g., capture for new ideas).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already indicate read-only, idempotent, and non-destructive behavior. The description adds valuable context: it explains the ranking method, default exclusions (archived, checkpoints), query_mode behavior including error raising on syntax failure in 'raw' mode. No contradictions with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (about 150 words) and front-loaded with the core purpose. Each sentence adds essential information: search technology, return values, scope, exclusions, query_mode details. No redundancy or fluff.
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 complexity (7 parameters, 0% schema coverage) and presence of an output schema, the description covers key behaviors (ranking, returns, exclusions, query modes). It omits details on sorting and precise parameter formats, but the output schema can supplement return information. Overall, it provides sufficient context for an agent to use the tool effectively.
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% schema description coverage, the description must compensate, and it does significantly. It explains the purpose of include_archived, include_checkpoints, and query_mode, along with detailed behavior for 'auto' vs 'raw'. However, it does not detail the expected format of 'query' or 'since', leaving some ambiguity for those parameters.
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 performs full-text search on ideas with specific technology (FTS5 + bm25 ranking) and returns snippet, score, and id. It distinguishes from siblings like 'list' or 'get' by focusing on search. The verb+resource combination is specific and unambiguous.
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 provides context on parameter usage (e.g., scope optional, archived excluded by default, include_checkpoints) but does not explicitly contrast with sibling tools or state when not to use it. The guidance is implied through parameter descriptions but lacks direct alternative recommendations.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations provide read-only, non-destructive, idempotent hints. Description adds value by specifying return fields (notes and outbound links). No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no unnecessary words. Front-loads action and scope. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Output schema exists, so return format details are not needed. Description fully covers what the tool does given its simplicity and schema coverage.
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?
Though schema has 0% coverage for 'id' parameter, description implicitly defines it as the idea identifier. With only one required param, this is sufficient compensation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states verb 'Get', resource 'idea', qualifiers 'by id', and includes what is returned ('notes and outbound links'). Distinguishes from sibling tools like 'list' and 'search'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Implicitly clear: use when you need a single idea's details by its ID. No explicit exclusions or comparisons, but context with sibling tools makes it straightforward.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, non-destructive, idempotent behavior. Description adds value by specifying return values and 'cheap' hint. No contradictions. Additional detail like 'fast' could have been included, but overall good.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: first states purpose and return, second states use case. No unnecessary words, highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple health probe with no parameters and output schema existing, the description provides enough context: what it returns and when to use. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is trivially 100%. Baseline for zero parameters is 4. Description does not need to add parameter semantics.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states it is a 'Cheap health probe' that returns specific info (server name, package version, store path) and confirms server connectivity. Distinguishes from sibling tools which are for data operations like 'dump' or 'get'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use to confirm the ideahub_mcp server is connected and responsive.' Provides clear context for use, though it does not mention alternatives or when not to use. Given the simplicity, this is sufficient.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations confirm mutating (readOnlyHint=false) and idempotent (idempotentHint=true). Description adds rich behavioral details: 5-second dedup window, SHA-256 dedup beyond window, tag merging, and 'dup_attempt' note. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Description is long but well-structured with 'Use when:' and clear breakdowns. Each sentence provides essential information. Slightly verbose due to detailed dedup rules, but efficiency is high given complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers purpose, usage, parameter behaviors, deduplication, and return value. Explains edge cases (fire-and-forget, raising candidates) and provenance. Almost no gaps remain for the agent.
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 0%, but description compensates: states 'content is required', explains defaults for scope/actor, normalizes task_ref to kebab-case, and documents candidates (default 5, max 10, 0 to skip). Missing detail on tags and originator, but still adds significant value.
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 'Capture a new durable idea' and distinguishes the tool from sibling 'checkpoint' by specifying when to use each. It also mentions the return value (candidates), making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly lists conditions for use ('stable synthesis', 'reusable pattern', 'standalone idea') and contrasts with 'checkpoint'. Provides guidance on 'candidates' parameter (set to 0 for fire-and-forget, raise to 10 for triaging) and explains deduplication behavior.
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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