@chaosintelligence/mcp

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by Chaos-Intelligence-Inc

Overview Schema Related Servers Score Discussions

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Server Quality Checklist

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Latest release: v1.0.0
Disambiguation4/5
Most tools target distinct resources (thoughts, streams, pages, posts) with clear actions. The main potential confusion is among thought retrieval tools (list_thoughts, search_thoughts, search_similar, list_recent_thoughts), but their descriptions clarify the differences between filtering, semantic search, and recent activity.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern in snake_case (e.g., search_streams, get_post, create_thought, update_page). Plural nouns are used for listing/searching, singular for getting a specific item, which is a predictable and uniform convention.
Tool Count3/5
With 25 tools, the server spans multiple domains (thoughts, streams, pages, Resonate posts, reference data), making it feel heavy but not outlandishly so. Each domain has a coherent set, though the sheer number edges toward the upper boundary of what is reasonable.
Completeness2/5
The surface is retrieval-heavy but lacks basic lifecycle operations: thoughts can be created but not updated or deleted, streams have no create/update/delete, and there is no way to create or delete posts. These gaps would force agents to work around missing functionality or fail at common tasks.
Average 3.8/5 across 25 of 25 tools scored. Lowest: 3.2/5.
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
- 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.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

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

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

How is the quality score calculated?

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

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

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

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

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of disclosing behavioral traits. It mentions 'public' posts, hinting at accessibility, but does not explicitly state that this is a read-only operation, nor does it describe pagination, return format, or any potential side effects. For a 10-parameter listing tool, this is a significant gap.
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 long, front-loaded with the core action, and avoids redundancy. Every word earns its place, making it highly concise while still conveying the essential 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?
Given the tool has 10 parameters, no annotations, and no output schema, the description is too brief. It fails to explain what the response contains, how pagination works, or any nuances of the filtering. The high complexity demands far more context than provided.
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 detailed descriptions for all 10 parameters. The description's generic mention of 'filters and sorting' adds no meaningful detail beyond what the schema already specifies. 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 tool's purpose: browsing public posts with filters and sorting. It uses a specific verb ('browse') and resource ('public Resonate posts'). While it doesn't explicitly name siblings, 'browse' implies a listing/filtering function distinct from 'search_posts'.
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 an explicit use case: 'Use this to find trending, recent, or popular posts.' This provides context for when to use it, but it does not mention alternatives or exclusion criteria, such as when to use 'search_posts' instead.
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 explains the high-level output but omits details like whether results are counts or percentages, if any authentication is required, or how the optional dimension parameter affects the response.
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 concise sentences with no filler, front-loading the main verb and resource while briefly elaborating on the return content.
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 tool is relatively simple with fully described parameters, so the description is adequate but not rich. It lacks usage guidance, output format details, and any behavioral caveats, which would be expected given the absence of an output schema and annotations.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already fully documents both parameters with descriptions and enum values. The description loosely maps to these dimensions but adds no new semantic detail beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb and resource ('Get demographic voting breakdown for a Resonate post') and enumerates the demographic dimensions it covers, distinguishing it from sibling tools like get_post or get_stats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. It implies a use case but does not explicitly contextualize it against 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?
With no annotations provided, the description carries the full burden for behavioral disclosure. It implies a read-only 'Get' operation but does not disclose that the optional 'vote_type' parameter filters results, nor does it mention return format or other behavioral details. Examples of reaction labels add context but do not cover filtering nuance.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences with no wasted words. The first states the primary function, the second provides useful examples of reaction labels, earning 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?
For a simple tool with one optional parameter and no output schema, the description covers the core purpose and gives helpful examples. However, it omits mention of the vote_type filter and does not clarify whether 'all' reaction types vary by vote type, leaving a small but real completeness gap.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the 'vote_type' parameter fully documented in the schema. The description adds no parameter information, but the schema already defines the enum and its filtering purpose. Baseline of 3 is appropriate because the schema does the heavy lifting.
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 ('Get') with a clear resource ('all available reaction types') and provides context ('used on Resonate posts'). It clearly distinguishes itself from sibling tools by naming a unique resource not covered by any sibling.
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 given on when to use this tool vs alternatives, nor any mention of when not to use it. The description only states what it does, leaving usage context entirely implicit.
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 safety and behavior. It mentions the use of AI embeddings, but does not describe output format, ranking, result thresholds, or any side effects. As a read operation, it's safe, but the description lacks substantive behavioral context beyond the 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?
Two sentences, immediately front-loaded with the tool's purpose, with the second sentence adding usage context. No redundant 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?
With full schema coverage and a simple read operation, the description is adequate but missing details about return output and any limitations. The absence of an output schema increases the burden, which is not fully met.
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?
All three parameters are fully described in the schema, so the description adds no additional parameter meaning. It earns the baseline of 3 given the complete schema 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 tool finds thoughts semantically similar to a text query using AI embeddings, which is specific and distinct from keyword search. However, it does not explicitly name alternative tools like search_thoughts for comparison, so it doesn't fully distinguish from siblings.
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 for when to use it ('Great for finding related ideas and concepts'), but does not mention when not to use it, nor does it reference alternative sibling tools. The usage is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It transparently states this is a read operation and enumerates the data shown (votes, reactions, demographics). However, it does not disclose pagination behavior, sorting nuances, potential data delays, or whether 'your content' includes drafts or only published posts. For a get operation, the gaps are moderate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the action and scope, followed by the data categories. Every clause carries useful information with no filler or redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a low-complexity read tool with three optional pagination/sorting parameters and no output schema, the description adequately conveys the returned categories. It might mention the specific demographic dimensions, but the schema covers mechanics. The lack of annotations is balanced by the simplicity and high schema 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 covers 100% of parameters with descriptions (page, sort_by, per_page), so baseline 3 applies. The description adds context about the returned data but does not elaborate on how parameters affect the output beyond what the schema already states. No value added beyond structured fields.
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 'Get performance data for posts you published to Resonate' with specific verb, resource, and scope. It distinguishes from siblings like get_post (single post retrieval) and get_post_demographics (likely narrower focus), though it does not name alternatives explicitly as the high benchmark does.
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?
Usage context is implied: use when you want performance metrics for your own published posts. However, there is no explicit guidance on when not to use this tool or which siblings to choose instead (e.g., get_post_demographics for a specific post's demographics). The tone is clear but lacks direct exclusions or 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions semantic similarity but does not disclose whether the operation is read-only, how results are ordered, whether pagination exists, or any potential side effects. This lack of detail about return behavior and constraints leaves significant gaps for an 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?
The description is exactly two sentences, front-loaded with the core action ('Search your thoughts'), and every phrase adds value. It avoids redundancy and is appropriately sized for the tool's functionality.
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 11 parameters and no output schema, the description should explain what the response contains or how results are structured. It does not mention the return format, ordering by similarity score, or how to interpret the min_score parameter in the results. The description covers the input side but leaves the output side completely unspecified, which is incomplete 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?
Schema description coverage is 100%, so the schema already documents all 11 parameters. The description summarizes the filter categories (stream, category, classification, date range) which aligns with the schema, but adds no deeper semantic meaning beyond what the schema property descriptions already provide. Thus, it meets the baseline but does not exceed it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search your thoughts using semantic similarity combined with structured filters.' It uses a specific verb ('Search'), identifies the resource ('thoughts'), and distinguishes itself from siblings like list_thoughts or search_similar by emphasizing semantic similarity plus structured filters.
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 semantic search with optional filters by stream, category, classification, or date range. It implies when this is appropriate (semantic queries) but does not explicitly exclude alternatives or mention when not to use it, so it lacks a full exclusionary comparison.
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. 'Get' clearly indicates a read operation, and 'search for posts' adds search behavior. However, it does not disclose pagination behavior, default sorting, response structure, or limitations. The schema covers pagination defaults, but the description adds little beyond the name's implication.
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 concise sentences with no redundancy. It is front-loaded with the core purpose and then adds the distinct search capability, making every word earn 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?
For a 6-parameter tool with no output schema, the description provides a useful summary but omits mention of optional filters like vote_type, date ranges, and pagination. It is adequate for initial tool selection but not fully complete for understanding all capabilities and expected output.
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's mention of 'content text' aligns with the 'search' parameter, and 'upvoted or downvoted' maps to 'vote_type', but it adds no new meaning beyond the schema's own parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Get') and resource ('your voting history on Resonate posts'), clearly distinguishing it from sibling tools like get_my_post_performance or search_posts. The additional search capability is also mentioned, 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 Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving one's own votes and searching by content text, but it does not explicitly state when to use this tool over alternatives or provide exclusions. No references to sibling tools or alternative approaches are given.
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 burden of indicating behavior. It discloses that the result includes thoughts and child streams, which is useful. However, it does not mention that thoughts are paginated (via thoughts_page and thoughts_per_page), which is a notable behavioral detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence communicates the tool's core purpose and scope without excess words. It is concise and readable.
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 provides a high-level summary, but without an output schema and with pagination parameters present, it does not clarify that 'thoughts' are returned as a page (default page 1, 20 per page) rather than all thoughts at once. This leaves some ambiguity about the response shape.
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?
All four parameters are documented in the input schema with 100% description coverage, so the schema carries the parameter semantics. The description adds no param-specific detail beyond the schema, so the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Get'), the resource ('a stream by ID'), and the included content ('thoughts and child streams'). It distinguishes itself from sibling tools like search_streams and list_streams by specifying ID-based retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'by ID' implies this tool is for retrieving a specific stream when the ID is known, but it does not explicitly state when to prefer this over search_streams or list_streams, nor does it mention any exclusions 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?
With no annotations, the description carries the transparency burden. 'List' reasonably implies a read-only operation, and the nesting note adds useful behavioral context, but pagination behavior, response shape, and permission requirements are not disclosed.
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 concise sentences, front-loading the tool's purpose and adding one relevant behavioral note. There is no redundancy or filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with five optional parameters and no output schema, the description provides basic purpose and hierarchy but omits usage guidance, pagination behavior, and return-value expectations. This leaves meaningful gaps for an agent to invoke 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 slight extra meaning by explaining streams as hierarchical folders, which supports parent_id semantics, but it does not substantially go beyond what the schema already documents.
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 uses a specific verb ('List') and resource ('your streams'), and defines streams as collections/folders for organizing thoughts. This clearly distinguishes the tool from siblings like get_stream (single stream) and search_streams (search behavior).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool lists the user's own streams and notes hierarchical nesting, which gives some usage context. However, it does not explicitly compare against search_streams or get_stream, nor does it state when not to use this tool.
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 discloses that the tool lists the user's own thoughts and returns paginated results, which adds some context beyond the schema. However, it omits how filters combine (AND/OR), the default sort order, and the structure of individual thought objects, leaving significant behavioral ambiguity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single 16-word sentence that encapsulates the action, resource, filter scope, and pagination. It is front-loaded with the verb, and every phrase adds value with no filler or repetition.
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 function and filter options, but with 11 optional parameters and no output schema, it omits important behavioral context such as default ordering, filter combination semantics, and the shape of the paginated response. It is adequate for simple usage but incomplete for sophisticated filtering scenarios.
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 provides a high-level grouping of filter types (stream, classification, category, date range, text search) that maps to the schema parameters, but it adds no syntax or interaction details beyond what the schema already documents. It is a helpful summary but not a substantive addition.
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 opens with 'List your captured thoughts', providing a specific verb and resource. It further distinguishes itself from sibling tools by enumerating filter dimensions (stream, classification, category, date range, text search) and noting pagination, which sets it apart from get_thought (single retrieval) and list_recent_thoughts (recency-limited).
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 implicitly conveys when to use the tool (when listing thoughts with optional filters) but does not reference alternatives such as search_thoughts or list_recent_thoughts, nor does it provide exclusions or comparative guidance. It leaves the agent to infer selection based on the stated capability.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must carry behavioral disclosure. It states that results include content previews, which is helpful, but omits details about sorting, pagination, default filtering, or the read-only nature of the operation. Minimal but not empty.
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, with two sentences front-loading the main purpose and return behavior. Every word adds value, and there is no 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 search tool with fully documented parameters, the description gives a basic overview and return type. However, it lacks mention of default status filtering, limit handling, or behavior with no matches, so it is only 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?
The schema provides complete descriptions for all three parameters (100% coverage). The description's mention of 'title keywords or content text' loosely aligns with the query parameter but adds no new detail beyond the schema's 'match against page titles and content'.
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 and target: 'Search pages by title keywords or content text.' It effectively distinguishes from sibling search tools for posts, streams, and thoughts, and from list_pages which likely returns all pages rather than matching ones.
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 use for finding pages by keyword but gives no explicit guidance on when to choose this tool over search_posts, search_streams, or list_pages. No exclusions or alternative recommendations are provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full transparency burden. It discloses the return contents (full content, metadata, source thought IDs) which is useful, but it does not explicitly state side effects, authentication requirements, or error behavior. 'Get' strongly implies read-only, but the description could be more explicit about non-destructiveness and edge cases.
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 that is effectively front-loaded with the verb and object, followed by concise detail about the output. There is no fluff or redundancy, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter get-by-ID tool, the description is reasonably complete: it names the parameter (implicitly, via 'ID'), states what is returned, and the schema clarifies the parameter type. However, with no output schema or explicit error-handling info, an agent might want more detail about the return structure or failure cases, but the description is sufficient for straightforward 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 input schema covers the only parameter page_id with a description ('The page ID to retrieve'), achieving 100% schema coverage. The description simply repeats the notion of 'by ID' without adding format constraints, examples, or additional semantic context. Baseline 3 is appropriate because the schema already does the heavy lifting.
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 ('Get'), the resource ('a single page'), and the specific scoping ('by ID'), while also enumerating what is returned ('full content, metadata, and source thought IDs'). This distinguishes it from sibling get tools like get_post or get_stream by explicitly naming 'page' and its unique payload.
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 (use when you need a single page by ID) but does not provide explicit guidance on when to choose this tool over alternatives such as search_pages or list_pages. There are no when-not-to-use conditions or named siblings, so the guidance remains implicit rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It indicates a read operation ('Get') and discloses the scope of returned data (votes, reactions, topic cluster, entities), but does not mention authentication, rate limits, errors, or behavior for deleted posts.
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, front-loaded sentence with no filler. Every word adds meaning, and the most important verb and object appear first.
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 low complexity (1 parameter, no annotations, no output schema), the description is sufficiently complete for an agent to select and invoke the tool. It clearly states the purpose and the key return fields, though it could mention whether the full post body is included.
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 schema already describes post_id as 'The post ID to retrieve' (100% coverage). The tool description adds no additional parameter-specific information, so it remains at baseline without enhancing the schema's meaning.
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 ('Get') and resource ('full details for a single Resonate post'), and enumerates the included content ('votes, reactions breakdown, topic cluster, entities'). This clearly differentiates it from sibling tools like list_posts, search_posts, or get_reactions.
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 use when a complete view of one post is needed, but does not explicitly state when to use this versus alternatives such as get_reactions or get_post_demographics. No exclusions or alternative recommendations 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, and the description offers no behavioral details beyond the purpose. It doesn't disclose that this is a read-only operation, the ordering of results, or how the limit interacts with the response. The description adds little over the tool's name and schema, so it fails to carry the transparency burden.
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 entire description is two short sentences. The first sentence immediately states the action, and the second provides the alternative context. No redundant or extraneous 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?
For a simple one-parameter read tool, the description covers the core purpose and a usage scenario. It doesn't describe the output shape or explicitly state that results are ordered, but the simplicity and schema coverage make it sufficiently complete for most agents.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema fully documents the single 'limit' parameter with default, min, max, and description, giving 100% schema_description_coverage. The description adds no parameter-specific information, but the baseline of 3 applies since the schema handles parameter semantics completely.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the verb 'get' and clearly specifies the resource 'most recently captured thoughts.' It also explicitly distinguishes itself from sibling tool list_thoughts by calling itself 'A simpler alternative to list_thoughts,' which meets the sibling differentiation criterion.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'when you just want to see recent activity' gives a clear context for when to use this tool compared to list_thoughts. It names list_thoughts as an alternative but doesn't explicitly state when not to use this tool (e.g., when you need filtering or full history), so it's clear but lacks exclusions.
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 burden of conveying safety and behavioral traits. 'Search' and 'Returns matching streams' imply a read-only operation, but it does not disclose pagination, ordering, or access requirements. This 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 two short sentences with no superfluous details. 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?
For a simple search tool with only two parameters, the description gives enough to understand the basic functionality. However, with no output schema or annotations, it lacks details on result format, pagination, and edge cases, leaving some 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 coverage is 100%, and both parameters are described in the schema. The description's mention of 'by name or description' echoes the query parameter's schema description, adding no new information beyond what the schema already provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Search' and identifies the resource ('streams') and search criteria ('by name or description'). It clearly distinguishes this tool from siblings like list_streams (all streams) and get_stream (single stream by ID).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'Search your streams' establishes a clear context for when to use this tool (when you need to find streams by text). However, it does not explicitly mention alternatives or exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the behavioral disclosure burden. It states what is returned but does not explicitly say that it is a read-only operation or mention any side effects, permissions, or error conditions. While 'get' implies read-only, explicit transparency is lacking.
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, tight sentence that delivers the essential information without fluff. It is front-loaded with the verb and resource, and every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter retrieval tool with no output schema and no annotations, the description is reasonably complete. It specifies the input and the expected return contents. It does not discuss when to choose this over similar tools, but the simplicity of the tool makes the description adequate.
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% (thought_id is described as 'The thought ID to retrieve'). The description adds minimal meaning beyond the schema by clarifying that the ID refers to a thought, but this is already evident from the parameter name and schema description. 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 uses a specific verb ('Get') and resource ('thought by ID'), and details exactly what is returned (content blocks, classification, category, streams). This clearly distinguishes it from sibling tools like list_thoughts and search_thoughts, which serve different retrieval purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The phrase 'specific thought by ID' implies the primary use case: when you have a known thought ID and need its full details. It does not explicitly mention alternatives like search_thoughts or list_thoughts, but the context is clear enough for an agent to infer when to choose this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It adds useful context about heat scores and sentiment, implying a read-only operation via the verb 'get', but it does not discuss pagination, default limits, or the fact that the status filter supports additional states like 'emerging' or 'archived'.
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 concise sentences that are front-loaded with the core purpose. Every word adds value, with no fluff or repetition of schema details.
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 moderate complexity (three optional parameters, no output schema), the description adequately covers what the tool does and what it returns (heat scores, sentiment). The schema fills in parameter details. A minor gap is that the description implies only trending/active while the schema allows other statuses, but this is not a major omission.
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 full descriptions for all three parameters (limit, status, sort_by) with 100% coverage. The description adds no additional parameter-specific meaning, so the 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 opens with 'Get trending and active topic clusters from Resonate', which clearly identifies the action (get) and the resource (topic clusters) with a specific source. The second sentence elaborates on what the clusters represent, distinguishing this from sibling tools that handle posts, streams, or thoughts.
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 helpful context by specifying 'trending and active' topics, indicating when this tool is appropriate. However, it does not explicitly mention alternatives or when not to use it, lacking exclusions or comparisons to sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what information is returned (current usage, rate limits, reset timing) and implies a read-only operation through 'Get'. However, it does not explicitly state that it is safe/read-only or discuss any side effects, permissions, or rate limits on the endpoint itself. Some behavioral context is present but incomplete.
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, front-loaded with the main purpose and followed by a brief use case. Every word earns its place; there is no redundancy or filler. This is a model of concise, well-structured tool documentation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity of the tool (0 parameters, no output schema), the description provides adequate context. It enumerates the types of data returned (current usage, rate limits, reset times), which compensates for the missing output schema. It also suggests a common use case. This is complete for the tool's complexity.
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 coverage is 100% (empty object). Per guidelines, a baseline of 4 applies for zero parameters. The description does not add parameter-specific detail because none exist, but it clarifies the output content, which is not parameter semantics. The baseline 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 tool's function: 'Get your API usage statistics including current usage, rate limits, and when limits reset.' It specifies the resource (API usage) and the action (get), making the purpose clear. However, it does not explicitly differentiate from sibling tools such as get_stats, relying on the uniqueness of 'usage' rather than naming alternatives.
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 a clear usage context: 'Useful for monitoring your API consumption.' This implies when to use the tool. It does not mention exclusions or alternatives, but the guidance is sufficient for a straightforward, parameterless tool.
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 for behavioral disclosure. It discloses a key side effect: 'Thoughts are automatically enriched with AI classification, categorization, entity extraction, and embeddings in the background.' This adds useful context about asynchronous processing. However, it does not mention return values, permissions, failure modes, or reversibility, leaving notable gaps for a create 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 two sentences with no fluff. The first sentence front-loads the core purpose and content types; the second adds the required condition and a valuable behavioral note. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a creation tool with no output schema and no annotations, the description covers the essential context: what it creates, required inputs, and background enrichment. The schema handles parameter details. However, it omits information about what the tool returns or how errors are handled, which would be useful for an agent invoking 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 coverage is 100%, so each parameter is already well-documented (e.g., max lengths, stream precedence). The description adds one critical cross-parameter constraint: 'At least one content type is required', which is not enforced by the schema but is essential for valid usage. This goes beyond the individual parameter descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool's verb ('Capture') and resource ('a new thought'), and specifies the three content types (text, images, links). This distinguishes it from sibling tools like get_thought, list_thoughts, and search_thoughts, which are all read operations. The purpose is unambiguous and specific.
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 states an important usage condition: 'At least one content type is required', guiding the agent on necessary input. It also implies this is the tool for creating thoughts, distinct from the read-only siblings. However, it does not explicitly name alternative tools or state when not to use it, so a full exclusion is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral disclosure. It implies a read-only list operation ('Get all available categories') and gives examples, but does not specify the return format (e.g., list of strings) or any edge cases. It is adequate but not rich in detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, well-structured sentence that front-loads the primary action ('Get all available categories'), includes examples, and ends with a clear usage directive. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with no parameters and no output schema, the description provides sufficient context: it names the resource, gives examples, and explains the use case. It could mention the exact data type of categories, but the current level is adequate for an agent to invoke and interpret the result.
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, so the baseline is 4. The description adds value by providing example values and the purpose of the returned categories, which helps the agent understand the context even though no parameters are needed.
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 retrieves all available categories and provides concrete examples (Technology, Business, Health). It also indicates the purpose (filtering thoughts), distinguishing it from sibling tools that operate on streams, posts, or pages.
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 gives explicit guidance: 'Use this to discover category names for filtering thoughts.' This clarifies the intended use case, though it does not contrast with alternative tools or mention 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?
With no annotations, the description carries the full burden of behavioral disclosure. It does reveal the output composition (summary statistics including count, breakdowns, date range, stream count) and implicitly indicates a read-only operation. However, it does not explicitly state that this is a read-only, non-mutating operation, nor does it mention any potential performance implications or data freshness considerations.
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 that immediately states the action and resource, then enumerates the specific output components. Every word contributes value with no redundancy or filler.
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 (no parameters, no output schema, no annotations), the description provides a reasonably complete picture of what the tool returns. It lists the key statistics, though it could slightly improve by clarifying whether the stats are global or per-user, but 'your captured thoughts' implies the user's scope, making it 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 the schema coverage is 100% (empty properties). According to the baseline for 0 params, the description gets a 4; it adds no parameter details because there are none, and the description focuses appropriately on the output rather than inputs.
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: to get summary statistics about captured thoughts. It specifies the exact breakdowns included (total count, classification, category, date range, stream count), making it distinct from sibling tools like list_thoughts or get_thought which return individual items or lists.
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 clearly implies the use case: when an aggregated overview of thought statistics is needed rather than individual thought details. It does not explicitly mention alternatives or exclusions, but the context is unambiguous and sufficiently differentiates it from sibling tools like get_usage or list_recent_thoughts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden. It discloses that the tool returns only metadata, not full content, and implies a read-only operation via 'List'. It also scopes to 'your' pages, which is a behavioral constraint. It doesn't mention side effects or auth requirements, but for a list operation these are less critical.
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 long, with the first sentence stating the purpose and filters, and the second clarifying the return format. It is front-loaded, contains no redundant wording, and every phrase adds value.
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 list tool with 5 optional params and no output schema, the description provides enough context: it states what is returned (metadata only) and the scope. It doesn't enumerate metadata fields, but that's not necessarily required for a list operation. The pagination and sorting details are already in the schema, so the description is sufficiently complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All 5 parameters are fully documented in the schema with descriptions, defaults, and enums (100% coverage). The description only summarizes these filters ('status, pinned state, pagination') without adding extra semantics or usage nuances. Baseline 3 is appropriate since the schema already does the heavy lifting.
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 'generated pages', with a parenthetical defining pages as 'documents created from thoughts' to distinguish from sibling tools like list_thoughts. It also clarifies the return scope ('page metadata without full content'), 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 Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description clearly sets the context: listing the user's own pages with optional filters. It does not explicitly mention alternatives or exclusions, but the parenthetical about pages being created from thoughts helps differentiate from similar list tools. No direct 'use this instead of X' guidance, but it's adequate for common usage.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses the key behavioral trait of semantic similarity (as opposed to keyword search) and restricts scope to 'public' posts. It could mention return format or pagination, but for a simple search tool this is sufficient behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core purpose, and every word earns its place. There is no redundant or vague filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is a simple search with 3 well-described parameters and no output schema. The description covers what it does and how to use it. It could mention the output type (list of posts) but that is reasonably implied by 'search posts' and the sibling context. A score of 4 is appropriate.
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% – all three parameters (text, limit, min_score) have descriptions. The description adds no additional parameter semantics beyond the schema, so the baseline of 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose with a specific verb ('Search'), resource ('public Resonate posts'), and method ('semantic similarity'). It differentiates from sibling search tools by explicitly naming 'posts' as the target, making it distinct from search_streams, search_thoughts, and search_pages.
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 second sentence provides clear usage context: 'Find posts about any topic by describing what you are looking for.' This explains the intended use case but does not explicitly name alternatives or exclusion criteria. Since the resource is clear, it is nearly as helpful as an explicit alternative statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses that the edit is direct and not AI-regenerated, and that at least one field must be provided. However, it does not explicitly state that omitted fields are preserved, nor does it mention error behavior, permissions, or idempotency, leaving some behavioral uncertainty.
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 three concise sentences, each earning its place. It front-loads the action, adds a clarifying behavioral note, and provides the critical usage constraint without redundancy or filler.
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 straightforward update tool, the description covers the essential aspects: what can be updated, the direct-edit mode, and the parameter requirement. With no annotations or output schema, it could further enhance completeness by explicitly stating that unspecified fields remain unchanged and indicating what happens for invalid page_id, but the current level is adequate.
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 already describes all parameters with meaningful descriptions (100% coverage), so the baseline is 3. The description adds valuable parameter semantics by explicitly stating the 'at least one of title, content, or short_description' constraint, which is not enforced by the schema (only page_id is required). This extra guidance justifies a higher score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Update' with the resource 'a page's title, content, and/or short description', clearly stating the tool's core function. It distinguishes itself from other tools by clarifying this is a direct edit without AI regeneration, which is useful given the sibling set includes read/search tools but no other update tool.
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 this tool: for direct edits without AI regeneration, and it states the requirement to provide at least one of title, content, or short_description. However, it does not explicitly name alternatives or describe when not to use this tool, which prevents a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the transparency burden. It communicates a read-only enumeration operation ('Get all available...') and includes example values, giving the agent a clear expectation of the output. It does not discuss edge cases or format, but for a simple list tool this is adequate.
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 short sentences: the first defines the tool and provides examples, the second explains its use case. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description fully covers what the agent needs: it names the resource, provides examples, and states how to use the result (for filtering thoughts). No critical information is missing.
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, so the baseline is 4. The description adds no parameter-specific meaning but is unnecessary since there are no parameters to clarify.
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 function: 'Get all available thought classifications/types' with concrete examples (task, idea, theory, question). This distinguishes it from sibling tools like get_categories and search_thoughts by specifying it retrieves classification names for filtering thoughts.
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: 'Use this to discover classification names for filtering thoughts.' It does not explicitly mention alternatives or when not to use it, but the purpose is well-scoped and distinct from siblings.
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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