signalis-mcp

Server Quality Checklist

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Latest release: v1.0.1
Disambiguation4/5
Most tools target distinct resources, but get_brief and get_latest both return digest content, and get_pulse_narratives vs get_pulse_narrative require careful reading. Descriptions clarify the differences, so confusion is unlikely but possible.
Naming Consistency4/5
The dominant pattern is get_<resource> with clear nouns (brief, index, sample, latest, history, narratives, etc.). The one outlier is submit_feedback, which uses a verb instead of get, but the rest are highly consistent.
Tool Count5/5
10 tools is well-scoped for an intelligence API that offers free instant access, paid historical data, pulse narratives, and raw content. Each tool covers a meaningful endpoint without redundancy.
Completeness4/5
The toolset covers the core lifecycle: index polling, sample, latest digest, history, feedback, and pulse details. Missing a way to fetch a specific free digest by ID or search could slow agents, but most workflows are supported.
Average 4.1/5 across 10 of 10 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 1 commit 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.
This repository includes a glama.json configuration file.
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?
With no annotations provided, the description carries the burden of behavioral disclosure. It explicitly states that the tool uses GET (read-only), requires no API key or wallet, and returns specific content. This goes beyond a simple function name by providing access and resource details. It does not mention rate limits or error handling, but for a simple read operation this is adequate transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long and front-loads the essential information: what the resource is, what it contains, the endpoint, and access requirements. Every word adds value, with no redundant or vague phrasing. It is highly concise while remaining informative.
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 parameterless GET endpoint, the description covers the main aspects: the resource, output items, and access conditions. It is largely complete. However, since there is no output schema, it could provide a little more detail on the sentiment format or possible empty responses, but this is a minor gap given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and the schema is empty, so there are no parameter semantics to explain. The description adds no parameter-related information, which is appropriate. It instead describes the output, but this is not required for this dimension. The baseline for 0 parameters is 4, and the description does not detract from it.
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 identifies the tool as retrieving the 'Current Master Intelligence digest brief' and specifies its contents: title, executive summary, and overall sentiment. It also includes the API endpoint, making the resource unambiguous. It does not explicitly contrast with sibling tools like get_intelligence_history or get_pulse_digests, so it misses the top score.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
There is no guidance on when to use this tool versus the sibling tools. While the word 'Current' implies it is for the latest brief, it does not state when to use alternatives for historical data or other intelligence types. The only usage condition ('FREE, no wallet or API key required') addresses prerequisites, not selection criteria.
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 description thoroughly discloses unusual behavioral traits: the $0.01 x402 payment, USDC on Base settlement, the compute-first/settle-after error policy, the PRIVATE_KEY requirement, and the return of 402 price terms without a key. Since no annotations are provided, this transparency is essential and well-executed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is somewhat repetitive, mentioning payment twice ('PAID $0.01 via x402' and 'Pays USDC on Base via x402'). It also buries the core purpose after billing information, making it less front-loaded than ideal. Still, it is brief and covers necessary points.
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 no-parameter tool with no annotations and no output schema, the description covers the essential operational aspects: what is returned, payment mechanics, error handling, and setup. It does not describe the output structure, but for a simple list-like tool this is acceptable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters, so no parameter explanation is needed. The baseline for zero-parameter tools is 4, and the description adds no unnecessary parameter details.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description states the resource as 'Active AI-business narratives with lifecycle stage and momentum,' and the tool name 'get_pulse_narratives' indicates retrieval. It distinguishes from the sibling 'get_pulse_narrative' by implying a collection of active narratives, though it lacks an explicit verb like 'retrieve' or 'list'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives such as get_pulse_narrative or get_pulse_digests. The description mentions payment setup and fallback to 402 terms but does not specify use cases or exclusions.
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, the description carries the full burden and does well by disclosing the paid nature ($0.02), compute-first settle-after guarantee ('never charged for an error'), and the behavior without a key (returns 402 price terms). This goes beyond the schema and helps set expectations.
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 three sentences long and every sentence adds critical information (cost, resource, payment behavior). It is reasonably front-loaded, though leading with pricing might be less intuitive than leading with what the tool returns.
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 zero-parameter tool with no output schema, the description covers the essential context: what it returns, the time window, cost, payment setup, and error behavior. It does not specify the output format, but that is a minor gap given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has zero parameters, so the baseline is 4. The description does not need to explain parameters but does mention the PRIVATE_KEY environment variable, which is relevant for usage. No additional param semantics needed.
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 identifies the resource ('raw scraped content items') and a specific scope ('last 4 hours'), which differentiates it from siblings like get_pulse_narratives or get_pulse_digests. Though the verb is implied rather than explicit, the tool name 'get' plus the description make the action clear.
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 time window ('last 4 hours') implies usage for recent content, but there is no explicit guidance on when to use this tool versus alternatives or when not to use it. The payment and setup details provide context but not selection guidance.
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?
With no annotations, the description carries full burden and excels: it discloses cost ($0.03 via x402), payment rail (USDC on Base), settlement model (compute-first, settle-after), error guarantee (never charged for an error), and auth prerequisite/fallback (PRIVATE_KEY; 402 without key). This is exemplary for a paid tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three sentences, front-loaded with price and scope, and every sentence provides useful information. However, 'PAID $0.03 via x402' and 'Pays USDC on Base via x402' are partially redundant, and the em-dash aside could be slightly condensed.
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 paid tool with one optional parameter and no output schema, the description covers cost, auth, error behavior, and historical scope. It does not clarify what happens when `since` is omitted or detail the digest contents/return shape, but it is otherwise sufficiently complete for an agent to invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter, `since`, is fully described in the input schema ('Return digests since this cursor/timestamp'), so schema coverage is 100%. The description adds no additional information about the cursor format or default behavior when `since` is omitted, but the baseline of 3 applies because the schema already documents it.
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 identifies the resource as 'Historical AI-business narrative digests' and the tool name provides the 'get' action. It indicates the temporal scope ('Historical'), which helps distinguish it from recent/latest tools, though it lacks an explicit verb like 'list' or 'fetch' and does not differentiate from siblings such as get_pulse_narratives.
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 clear operational context: it costs $0.03, requires PRIVATE_KEY for live use, and returns 402 price terms without a key. However, it does not explicitly state when to prefer this tool over alternatives or mention exclusions, so usage is implied rather than directly guided.
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 adds useful behavioral context — 'FREE, no wallet or API key required' — and the POST endpoint implies mutation. However, it does not disclose what happens after submission (e.g., response format, idempotency) or any rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
A single, front-loaded sentence that states the action, target, endpoint, and key requirement (no API key/wallet). Every word earns its place with zero 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 simple 4-parameter mutation with no output schema and no annotations, the description covers the essential purpose and auth requirement. However, it omits any mention of return values, duplicate prevention, or how comments/digestType fit into the submission flow, 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 every parameter has a description. The description adds nothing beyond the schema; 'master digest' maps to digestId, but no new semantics or relationships are introduced.
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 a specific verb ('Submit') and resource ('quality feedback on a master digest'), and even includes the endpoint. This clearly distinguishes it from the sibling get_* tools, all of which are read-only.
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: this tool is for submitting feedback, while all sibling tools are retrieval-oriented. It doesn't explicitly state 'when not to use' or mention alternatives, but the purpose is unambiguous.
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?
It discloses the HTTP method (GET), implying a read-only operation, and states that it is free and requires no credentials. No additional behavioral traits like rate limits or response sizes are mentioned, but with no annotations, it covers the essential access requirements.
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, information-dense sentence that states the content, endpoint, and access requirements without any fluff. It is appropriately sized for a no-parameter tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has no parameters and no output schema, the description provides sufficient context by describing the content (narratives, signals, markdown) and the endpoint. It does not detail response structure, but that might be secondary; overall it's complete for basic selection.
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 description rightly omits parameter details. The baseline score of 4 applies since there are no parameters to describe.
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 it provides the 'Full Master Intelligence Digest with narratives, signals, and markdown analysis' and specifies the exact endpoint GET /v1/intelligence/latest. The word 'Full' distinguishes it from sibling tools like get_brief or get_sample, making its purpose clear.
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 notes it is 'FREE' and requires 'no wallet or API key', indicating it's accessible without authentication. However, it does not explicitly compare when to use this over get_brief or get_index, nor does it state exclusions.
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?
With no annotations, the description fully discloses the tool's behavioral traits: it is a paid API ($0.03 via x402), settles in USDC on Base, uses compute-first settle-after so errors are free, and requires a PRIVATE_KEY for live calls. This is exceptional transparency, including failure modes and conditional behavior.
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 packs a lot of essential information into two sentences, including payment, historical scope, settlement method, error policy, and key requirements. It is dense but efficient, with no filler; however, the first sentence is somewhat complex with multiple clauses, slightly reducing readability.
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 description thoroughly addresses the tool's complexity: payment, authentication, error handling, and lookback window. It does not describe the return format or digest structure, but given no output schema and the tool's focused purpose, this is a minor omission. Overall, the description is complete enough for effective use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema provides 100% coverage with descriptions for both hours and limit. The description adds little beyond restating the lookback range (1-168 hours) already present in the schema. Since the schema does the heavy lifting, 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.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies the tool as providing historical Master Intelligence digests over a 1-168 hour lookback, which distinguishes it from sibling tools like get_latest. However, it lacks an explicit action verb (e.g., 'retrieve' or 'get'), relying on the tool name and noun phrase for the action.
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 operational guidance: set PRIVATE_KEY for a live API call, otherwise the call returns 402 price terms. The historical lookback context implies when to use this tool versus alternatives like get_latest, though it does not explicitly name alternatives or exclusions.
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, the description carries the burden. It discloses that the tool is a poll target and that it requires no wallet or API key, which addresses authentication and suggests a lightweight read operation. It lacks details on rate limits or error handling, but for a simple read-only endpoint this is acceptable.
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 every phrase adds value. It avoids redundancy and conveys purpose, usage, and access requirements efficiently.
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 low complexity (no parameters, no output schema), the description covers the essential aspects: what it returns, when to use it, and that it's free. A minor gap is not naming the specific fetching tool to use after detecting a new digest, but the description is otherwise complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are zero parameters and no input schema properties, so schema coverage is complete. The description adds context about the returned fields (master digest id, updatedAt, nextExpected time) and their purpose, enhancing understanding beyond the empty 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 returns the current master digest id, updatedAt, and nextExpected time, using the specific verb 'poll target'. This distinguishes it from sibling tools like get_brief or get_latest, which likely serve different content-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?
It explicitly advises 'Use it to detect a new digest before fetching,' giving clear when-to-use context. It does not mention alternatives or when-not-to-use, but the provided use case is actionable and 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?
The description discloses the cost ($0.01), payment method (USDC on Base via x402), error policy (never charged for an error), and behavior without a key (returns 402 price terms). This is rich behavioral disclosure beyond what annotations provide (none).
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 sentences with no wasted words. It front-loads the key paid nature, then describes the return content, and finishes with setup instructions. Every sentence 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?
Despite lacking an output schema, the description explains the return content (content items and source attribution) and covers payment/error scenarios, making it complete for a single-parameter tool. The combination of purpose, usage, and transparency is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema covers the single parameter 'id' with 100% coverage, describing it as 'Narrative id (from get_pulse_narratives)'. The description doesn't add parameter-specific details beyond referring to 'one narrative', so it meets the baseline without adding extra 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 the tool returns detail for a single narrative, including content items and source attribution. The verb 'Detail' and the qualifier 'one narrative' make the purpose specific and distinguish it from listing siblings like get_pulse_narratives.
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 usage context: set PRIVATE_KEY to pay via x402 on a live API, and without a key the call returns 402 price terms. It doesn't explicitly mention alternatives, but the 'one narrative' scope implies it's for fetching details for a specific narrative, and the schema references get_pulse_narratives for the id.
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, the description carries the full burden. It discloses that the tool is free, requires no wallet or API key, and is a sample, implying a read-only operation. This is valuable behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, consisting of three short sentences. Each sentence provides distinct value: what it is, when to use it, and access requirements. No wasted words.
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 zero-parameter tool with no annotations or output schema, the description fully covers the purpose, usage, and access constraints. It's complete enough for an agent to select and invoke the tool correctly.
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, making schema coverage trivially 100%. The description adds context about the sample's purpose and access requirements, which is sufficient given there are no parameters to document.
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 as a sample digest that shows the response structure, with the specific endpoint GET /v1/intelligence/sample. This distinguishes it from sibling tools that serve actual content (e.g., get_pulse_digests, get_latest).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states a clear use case: 'Use it to learn the contract before paying.' This provides context for when to use the tool, though it doesn't explicitly mention alternatives or exclusions.
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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