d3p MCP Server
Server Quality Checklist
Latest release: v0.1.0
- Disambiguation4/5
Most tools have distinct purposes, but there are a few overlaps: d3p_btc-price and d3p_bitcoin-price-in-gold-ounces both deal with Bitcoin price, and d3p_vibe-check and d3p_emoji-sentiment both analyze sentiment. The pipeline tools are distinct from the utility tools, but within the utility set, some boundaries are fuzzy.
Naming Consistency2/5Tool names mix conventions: some use hyphens (d3p_ext-search-v2, d3p_btc-price), some use underscores (d3p_vibe_check? Actually it's d3p_vibe-check with hyphen, but also d3p_list_services with underscore), and verbs vary (list, discover, check, execute). There is no consistent verb_noun pattern, and the prefix 'd3p_' is the only unifying element.
Tool Count3/5With 34 tools, the server feels slightly overloaded. The pipeline management tools (approx. 6) are well-scoped, but the remaining 28 utility tools range from essential (weather, search) to niche (cat-name-generator, roast-my-idea). The count is borderline heavy for a coherent set.
Completeness3/5The pipeline and service discovery tools seem complete (execute, validate, status, result, templates, discover, compatibility, price quote). However, the utility tools are a random collection with no clear domain coverage; for example, there are multiple sentiment tools but no tool to update or delete services. Significant gaps in covering any specific domain.
Average 3.7/5 across 34 of 34 tools scored. Lowest: 2.2/5.
See the Tool Scores section below for per-tool breakdowns.
- 0 of 1 community issues answered or closed 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
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This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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glama.jsonto the root of your repository:{ "$schema": "https://glama.ai/mcp/schemas/server.json", "maintainers": [ "your-github-username" ] }Then . Browse examples.
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How is the quality score calculated?
The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).
Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.
Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).
Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.
Tool Scores
- Behavior1/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, and the description does not disclose any behavioral traits such as side effects, authorization needs, rate limits, or what 'passes certification' implies operationally. The description is nearly silent on behavior beyond the basic action.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very short but includes extraneous metadata (category, cost, endpoint). It is concise but not well-structured for agent decision-making. The truncation indicates incompleteness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the return values might be documented elsewhere, but the description fails to provide enough context about input expectations or what the tool does in enough detail for an agent to use it confidently. The description is too sparse for a tool with one complex parameter.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage and only a generic 'params' string. The description mentions a 'query' parameter but is truncated and does not explain how to structure the JSON string or what other parameters might be available. This leaves the agent with minimal guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states it is a 'Third-party search that passes certification', so the basic purpose is clear, but it lacks specificity about what exactly is being searched (e.g., web, documents, APIs). The sibling tools do not directly overlap in naming, but the vagueness reduces clarity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. There is no mention of use cases, prerequisites, or what differentiates it from other search-like tools among the siblings. The description only provides metadata (cost, category) without functional guidance.
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?
Without annotations, the description only states it 'get's data, implying read-only behavior. No disclosure of auth requirements, error handling, or rate limits. The minimal description does not compensate for the missing annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is short but includes a redundant parameter line that repeats schema information. It could be more concise by omitting the parameter details, making it less efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema, the description need not detail return values, but it fails to cover error scenarios, prerequisites, or behavior for invalid inputs. The tool is simple, yet the context is incomplete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description repeats the parameter name and type from the schema without adding meaning. Schema coverage is 0%, so the description should provide additional context (e.g., format, allowed values), but it does not.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the tool retrieves a reputation score and breakdown for a d3p service, using a specific verb-resource pair. Differentiates from sibling tools like d3p_list_services (which lists services) and d3p_check_compatibility.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives. The description implies use for reputation queries but does not specify when not to use or mention any prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not disclose side effects, auth requirements, rate limits, or what happens to input data. The mention of 'Cost: 10 sats' is a behavioral hint but insufficient for full transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness2/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is verbose, including metadata like category, cost, and endpoint that could be elsewhere. The parameter list is useful but adds length. The first sentence clearly states purpose, but overall the description could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool that generates content, the description lacks specifics like which platforms are covered or what 'ready-to-post' means. An output schema exists (not shown) but the description does not hint at return format. It is adequate but leaves some context gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% as the schema only has a generic 'params' string. The description compensates by listing five required parameters (launch_date, product_description, etc.) with brief descriptions. However, this information is unstructured and mixed with other metadata, making it less effective than a proper schema would be.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates a 'complete 5-platform launch plan with custom, ready-to-post content', which is specific and actionable. However, it does not explicitly differentiate from sibling tools like 'd3p_roast-my-idea' or 'd3p_post-optimizer', so it loses some points for lack of sibling distinction.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives, such as 'd3p_post-optimizer' or 'd3p_client-closer'. There is no information about prerequisites, contextual hints, or when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It does describe the output (tier recommendations, psychological insights, copy) and mentions a cost of 10 sats, but does not disclose any side effects, rate limits, or error conditions. The behavioral transparency is adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately concise but includes metadata (category, cost, endpoint) that may be redundant. The parameter list is detailed but could be more structured. The first sentence is clear and front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that there is an output schema (not shown) and a single-arg input schema, the description does not clarify how to invoke the tool (passing a JSON string vs. individual parameters) or what the return format is. It lacks completeness for an agent to reliably invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only has a single 'params' string with no description, while the description lists five separate parameters with explanations, adding significant meaning. However, there is a mismatch between the schema expecting a JSON string and the description listing parameters individually, which could confuse an AI agent. The description compensates partially.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a complete pricing strategy with tier recommendations, psychological insights, and landing page copy. The verb 'Generate' is specific, and the resource is the pricing strategy. However, it does not differentiate from sibling tools that might also generate business advice.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not provide any guidance on when to use this tool versus alternatives. It lists required parameters but no context on when the tool is appropriate or when to avoid it. No explicit when-not-to-use or alternative recommendations are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must bear full responsibility for behavioral disclosure. It states it is an analysis tool with a cost, but does not describe side effects, authorization needs, or how the results are returned. Additionally, there is a discrepancy between the described parameters (constraints, product_description) and the actual schema (single 'params' string), which may mislead about tool behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single paragraph that includes necessary information but also redundancy (e.g., 'Parameters (pass as JSON string):' followed by listed parameters). It could be more concise and structured, such as listing parameters in a clearer format. Every sentence is not maximally efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite the presence of an output schema (as per context signals), the description does not explain what the tool returns. It also does not clarify how to properly embed the two described parameters into the single 'params' JSON string. For a tool with complexity, this lack of completeness hinders correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Although the schema only has one opaque parameter ('params'), the description clarifies that this string should contain two sub-parameters: 'constraints' and 'product_description', each with their own descriptions. This adds significant meaning beyond the schema, which has 0% coverage. However, the description implies these are separate parameters, which could confuse an agent expecting explicit properties.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it breaks down product ideas into MVP scope, identifying what to cut and ship first. This provides a specific verb and resource, but it does not explicitly differentiate from siblings like 'd3p_roast-my-idea' or 'd3p_launch-brief', which may have overlapping purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lacks any guidance on when to use this tool versus alternatives. It mentions a category ('analysis') and cost, but does not specify prerequisites, exclusions, or context where other tools would be more appropriate. No usage guidelines 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?
With no annotations provided, the description carries the full burden of behavioral disclosure. It fails to mention safety traits (e.g., read-only, destructive potential), rate limits, authentication needs, or side effects. The cost and endpoint are given but do not cover behavioral expectations for an AI agent.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively concise, with the main purpose front-loaded. It includes optional metadata (Category, Cost, Endpoint) that may be redundant if available elsewhere, but overall it is not overly verbose. A slight improvement would be removing metadata that duplicates tool attributes.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), the description does not need to detail return values. However, it omits explaining the actual output structure (e.g., the 6 categories and letter grades). The parameter handling (JSON string) could be clearer. The description is adequate but leaves gaps for a complex tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% parameter description coverage and a single 'params' string expecting a JSON. The description clarifies that 'url' is required inside this JSON, adding meaning beyond the schema. However, this conflicts with the schema's default of '{}' and zero required parameters, potentially confusing the agent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it audits URLs for SEO and AI discoverability, analyzing meta tags, schema markup, and performance with letter grades across 6 categories. The verb 'audits' and resource 'URLs' are specific, and it differentiates from siblings by focusing on SEO/AEO, unlike other d3p tools that handle search, pricing, or weather.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a 'Category: analysis' label but offers no explicit guidance on when to use this tool versus alternatives. There are no exclusions, prerequisites, or comparisons to sibling tools. The cost is mentioned but does not serve as a usage guideline for selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description must carry the burden of behavioral disclosure. It mentions the output format (vibe score 1-10, energy classification, analysis) and that cost is 10 sats. However, it does not explain edge cases like empty text, error behavior, or the fact that the tool expects a JSON string parameter.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively concise at 4 sentences, with the core purpose stated first. The extra details (cost, endpoint, parameter hint) are relevant but add slight redundancy. It is well-structured and easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and the presence of an output schema, the description covers the return values adequately. However, it lacks details on parameter construction (how to pass the JSON string), edge cases, and error handling, leaving gaps for an AI agent to properly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% because the schema only shows a generic 'params' string. The description attempts to compensate by specifying a nested 'text' parameter and its requirement. However, it contradicts the schema (description says 'required', schema shows no required parameters) and does not fully clarify the JSON string format.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool performs sentiment/vibe analysis on text, returning a vibe score, energy classification, and analysis. However, it does not distinguish itself from sibling tool 'd3p_emoji-sentiment' which likely performs similar analysis, so differentiation is lacking.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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, nor any context about when it is appropriate or not. The category and cost are mentioned but do not serve as usage guidance.
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 only states the core function and adds cost/endpoint info, but does not explain side effects, authentication needs, rate limits, or whether the operation is read-only or destructive. Behavioral transparency is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: one sentence for purpose, one line for metadata, and one line for the parameter. Every sentence adds value without redundancy. It is front-loaded with the essential action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with one parameter, but the description does not address what happens with invalid status codes, how 'fix suggestions' are structured, or how to interpret the output (though an output schema exists). The inconsistency with the required parameter also undermines completeness. Adequate but leaves gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only specifies a 'params' string with no description (0% coverage). The description adds meaning by explaining that the JSON string should contain a required 'status_code' integer. However, it contradicts the schema which has no required fields, and does not clarify if other properties are possible. Partial compensation with an inconsistency.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does 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 ('Translate') and resource ('HTTP status codes'), including the output ('human-readable explanations with fix suggestions'). It is distinct from sibling tools which cover different domains like search, pricing, or validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives, when not to use it, or specific prerequisites. The mention of 'Category: data' is too vague to provide actionable usage direction, and no exclusions or use cases are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so the description carries full burden. It mentions category, cost, and endpoint but does not disclose side effects, required permissions, or behavior on missing input.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded with purpose. The parameter format is clearly stated. Minor waste: repeating 'Parameters (pass as JSON string)' could be integrated, but overall efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having an output schema, the description does not clarify the expected format of the input JSON or handle the mismatch where product_description is described as required but the schema has no required parameters. This could confuse an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0%, but the description explains that parameters are passed as a JSON string and lists the required 'product_description' field. This adds essential meaning beyond the bare schema that only has a generic 'params' string.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states what the tool does: analyzes a product/service and provides monetization strategies, sales pitch, and distribution plan. This is a specific verb-resource pair that distinguishes it from siblings like pricing-coach or roast-my-idea.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The description does not mention any prerequisites, exclusions, or similar tools among the many siblings.
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?
The description discloses core behavior: it compresses by keeping first and last messages and reports reduction percentage. It also notes cost and endpoint. However, it does not cover edge cases (e.g., empty or single-message arrays), side effects (mutability), or return format details (partially covered by output schema). With no annotations, more detail is warranted.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two clear sentences plus a metadata line. The key action is front-loaded. No redundant information; each part earns its place. A minor improvement would be structuring metadata as a list, but it's adequately scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has one string parameter with a JSON payload and an output schema exists, the description covers the main intent and parameter structure modestly. However, it lacks explanation of required vs optional fields, message format, and does not provide an example. The presence of an output schema partially mitigates this, but the description could be more complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% coverage (only a generic 'params' string), but the description adds meaning by specifying 'messages' as an expected array field. This improves usability but does not fully compensate: it lacks details on message format, optional fields, or other potential parameters within the JSON string.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool compresses an array of chat messages by keeping the first and last, and reports reduction percentage. It specifies the resource (chat messages) and the action (compress), making the purpose unmistakable. Although sibling differentiation is not explicit, the unique function is obvious.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 alternatives. It does not mention prerequisites, constraints, or exclusions. The description lacks explicit when-to-use and when-not-to-use instructions, making it difficult for an agent to decide contextually.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions cost (5 sats) and endpoint, which adds transparency. However, it does not state whether the tool has side effects, stores data, or imposes rate limits. Behavioral coverage is partial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is brief and front-loaded: first sentence gives purpose, second lists metadata (category, cost, endpoint) and parameter. No wasted words. However, it could be more structured (e.g., bullet points).
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the single parameter and the presence of an output schema, the description covers the essential input format. It includes cost and endpoint. Missing details like expected output structure or usage limits are partly compensated by the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% coverage and only a generic 'params' string. The description explains that the string should be a JSON with a 'topic' field. This adds meaning, but the description implies a spice level rating without specifying it as a parameter, creating ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool generates 'platform-optimized shitposts' with a spice level rating. The verb 'generate' and specific resource 'shitposts' make purpose explicit. It distinguishes from sibling tools like d3p_roast-my-idea and d3p_eli5 by focusing on humor and low-quality posts.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when or when not to use this tool. It does not mention alternatives or context. For example, it does not say 'use for humorous content, not serious messaging' or compare to similar generators.
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 disclosing behavior. It states the tool is a conversion and mentions 'Cost: 5 sats', but does not discuss error handling, data sources, or any side effects. The behavioral disclosure is minimal but adequate for a simple conversion tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, including only relevant information (category, cost, endpoint, parameters). It is front-loaded with the purpose, and the parameter list is presented clearly. The inclusion of cost and endpoint adds context without bloating the description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists, the description does not need to explain return values. However, the description leaves ambiguity about the JSON string requirement despite stating 'pass as JSON string'. The mismatch between description (required params) and schema (no required params) introduces confusion. Overall, it covers essential aspects but lacks full clarity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only has a generic 'params' string, providing no parameter details. The description adds meaning by naming the two expected parameters (bitcoin_price_usd, gold_price_per_oz) and marking them required, though this contradicts the schema which has no required fields. The description does not provide formats, examples, or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's verb ('Convert') and resource ('Bitcoin's USD price to equivalent gold ounces'), making its purpose immediately apparent. It is well-distinguished from siblings like 'd3p_btc-price' which focus on Bitcoin price in USD.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for converting Bitcoin price to gold ounces, but lacks explicit guidance on when to use this tool versus alternatives (e.g., when you already have gold price in USD). No when-not-to-use or prerequisite information is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must disclose behavioral traits. It mentions the cost (10 sats) and the output components, but does not state whether the tool is read-only, requires authentication, or has side effects. Behavioral transparency is minimal.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description front-loads the purpose and then lists parameters. It includes some metadata (Category, Cost, Endpoint) that may be redundant, but overall it is well-structured and efficient. Could be slightly more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the existence of an output schema (not shown), the description does not need to explain return values. However, it omits the output format (e.g., JSON or text) and potential error handling. The instruction to pass params as a JSON string is helpful. Completeness is adequate but has gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only has a generic 'params' string with no properties, so schema coverage is 0%. The description compensates by listing four parameters (key_benefit, price_range, product_description, target_audience) with descriptions and required status. This adds significant meaning beyond the schema, though format constraints are missing.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate complete sales kit with cold email, follow-ups, objections, proposal, and pricing'. It uses a specific verb ('Generate') and resource ('complete sales kit') and lists components, distinguishing it from siblings like pricing-coach or scope-cutter.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for generating a sales kit but provides no explicit guidance on when to use it versus alternatives like pricing-coach or scope-cutter. No when-not-to-use or alternative references are given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden. It mentions cost (5 sats) and endpoint, but does not disclose whether the action is irreversible, requires authentication, involves AI, or has rate limits. The behavioral impact of 'optimize' is not fully explained.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with a clear first sentence stating purpose, followed by metadata (category, cost, endpoint) and parameter list. No redundant information, though the metadata could be considered additional but useful given no annotations.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the complexity of a JSON string parameter and the presence of an output schema, the description adequately explains input parameters but fails to describe the output format or behavior. It lacks details on possible values for 'goal' beyond listing them, and does not specify error handling or default behavior.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, but the description adds meaning by explaining that the single 'params' string should contain a JSON object with two required fields: 'goal' and 'post_content'. This compensates for the schema's lack of detail and clarifies the parameter structure.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Optimize social media posts for maximum engagement with strategic hashtags, timing, and reshare hooks.' It uses a specific verb ('optimize') and resource ('social media posts'), distinguishing it from sibling tools like 'd3p_roast-my-idea' or 'd3p_shitpost'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for optimizing posts but lacks explicit when-to-use or when-not-to-use guidance. It does not mention alternatives among siblings, nor does it provide context like prerequisites or limitations.
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 provided. Description implies a read-only operation ('Get'), but does not disclose any potential side effects, data freshness, or authentication requirements. For a simple retrieval, the transparency is adequate but lacks depth.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, enumerates returned fields, zero wasted words. Front-loaded with purpose and details.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and expected output described (base URL, manifest URL, payment mode, service count), the description is complete. Output schema exists but description aligns without needing to refer to it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist (schema coverage 100%). Baseline score applies as description adds no param-specific meaning beyond what schema already conveys—which is nothing. No additional context is needed.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it retrieves d3p protocol info, listing specific fields. It is distinct from sibling tools like d3p_list_services (which lists services) and d3p_discover (which likely discovers resources). However, it does not explicitly differentiate itself.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus siblings. While the zero-parameter nature makes usage straightforward, explicit context about its role (e.g., 'Use this to get static protocol configuration') is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavioral traits. It mentions cost (5 sats) and endpoint, but lacks details on rate limits, data freshness, required permissions, idempotency, or response format. The read-only nature is implied but not explicit. This is insufficient for a tool with no annotation support.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise, front-loading the purpose in the first sentence, followed by metadata (category, cost, endpoint) and parameter usage. Every sentence serves a clear function with no redundancy or filler. Ideal for quick parsing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that an output schema exists, the description does not need to fully explain return values, but it already lists the key data points. It covers the main functionality for a simple weather tool. Minor gaps (e.g., units, error behavior) are acceptable because of the output schema. Nearly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has a single 'params' string with no description (0% coverage). The description compensates by specifying that the JSON string must contain a 'location' field with a city name. This adds critical meaning beyond the bare schema. However, it does not state if location is required or provide format constraints, preventing a perfect score.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool returns current weather conditions including specific data points (temperature, humidity, wind, feels-like). It uses a specific verb ('Current weather conditions') and identifies the resource (any location). Although no sibling weather tools exist, the purpose is distinct and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5Does 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 or when not to use it. There is no mention of appropriate contexts, prerequisites, or exclusions. The agent is left to infer usage without any comparative or restrictive information.
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 full burden. It mentions 'Returns confidence score and warnings' and 'Cost: 10 sats,' which adds some behavioral context. However, it does not disclose rate limits, authentication needs, error handling, or any destructive impact. It is not misleading 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.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is moderately concise, mixing a plain sentence with a parameter block. It is functional but could be more structured (e.g., separating usage notes from technical details). The parameter info is front-loaded but followed by repeated 'Category:' and 'Cost:' lines that add clutter.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the core function and parameter structure, and an output schema exists (from context signals), so return values need not be explained. However, it lacks details on input constraints (e.g., text length), error conditions, and whether the tool modifies state. These gaps reduce completeness for paid tool usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only defines a single 'params' string property with default '{}', providing no semantics. The description compensates by explaining that 'params' should contain a 'response' string field for the AI-generated text. This adds essential meaning beyond the schema, making the tool usable.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze AI-generated text for hallucination risk based on linguistic markers.' It specifies the verb 'analyze' and resource 'AI-generated text for hallucination risk,' distinguishing it from sibling tools like d3p_vibe-check or d3p_emoji-sentiment, which focus on different analysis types.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no explicit when-to-use or when-not-to-use guidance. It only lists 'Category: analysis' and cost, implying it's suitable for hallucination detection but lacking exclusion criteria or alternatives. No sibling differentiation or context for when to avoid 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 must cover all behavioral traits. It discloses that the tool does not execute the pipeline, provides a cost estimate, and checks compatibility. However, it omits details about authentication needs, side effects (likely none), and output format, which are important for a validation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the core purpose and behavior. Every word adds value, with no unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given low schema coverage (0%) and no annotations, the description should provide more context. It references the execute tool's format but does not describe the output (though an output schema exists, it is not explained). The tool's behavior is clear, but input requirements and return values are under-documented.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'pipeline' has no schema description (0% coverage). The description only says 'Same input format as d3p_pipeline_execute', which is vague and does not explain the expected JSON structure, required fields, or constraints. The default '{}' is mentioned but not elaborated.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool performs a dry-run to check compatibility and cost estimation, avoiding actual execution. It explicitly distinguishes from d3p_pipeline_execute by contrasting dry-run vs. execution, making the purpose distinct.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly tells when to use (before executing) by stating 'without actually executing it' and references the alternative d3p_pipeline_execute. However, it does not provide explicit when-not-to-use scenarios or mention other sibling tools like d3p_pipeline_status, leaving some ambiguity.
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 discloses that price varies by demand, caller reputation, and priority, and lists priority multipliers. However, it does not state whether the tool is read-only, if there are side effects, or rate limits. For a price quote tool, read-only is likely, but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, with two sentences: one for purpose and one for parameter details. No redundant information. Front-loaded with the main action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool has one parameter and no annotations, but the description is moderately complete: it covers purpose, key parameters, and behavioral factors. However, it lacks usage guidelines and output explanation, and the output schema exists but is not mentioned. For a tool with 33 siblings, more context would be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has a single JSON string parameter 'params' with 0% schema coverage. The description adds meaning by listing expected fields: service_id (required), priority (optional with enum values). But it does not fully describe the JSON structure (e.g., if other fields exist) nor reference the output schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Get a dynamic price quote for a d3p service.' This distinguishes it from siblings like d3p_btc-price (bitcoin) and d3p_pricing-coach (advice). The verb 'Get' and resource 'price quote' are specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context (for pricing d3p services) but does not explicitly state when to use this tool versus alternatives like d3p_list_services or d3p_discover. No when-not-to-use guidance is 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?
With no annotations provided, the description carries full burden. It discloses the data source (CoinGecko), cost (5 sats), and endpoint, but does not mention rate limits, authentication, error behavior, or caching. The existence of an output schema reduces the need to detail return values, but more context on reliability and limitations would improve transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (three lines) and front-loads the core functionality. It includes metadata (category, cost, endpoint) that adds value without being verbose. Every sentence serves a purpose, but the meta-data could be integrated more naturally.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (1 parameter, known API) and existence of output schema, the description covers the basics: source, return type (price+change), and supported currencies. However, it omits details on update frequency, caching behavior, and error cases, which would be useful for an agent making informed decisions.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% coverage (only a generic 'params' string), so the description compensates by specifying the actual parameter 'currency' with examples (usd, eur, gbp, etc.). It also states to 'pass as JSON string,' which clarifies usage. However, it doesn't specify if currency is required or its default value, leaving some ambiguity.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool provides 'real-time Bitcoin price from CoinGecko with 24h change' and 'supports multiple fiat currencies,' making the verb (get) and resource (Bitcoin price) specific. It distinguishes itself from the sibling 'd3p_bitcoin-price-in-gold-ounces' by focusing on fiat currencies.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description does not explicitly state when to use this tool versus alternatives. The 'category: oracle' hint and mention of fiat currencies implicitly differentiate it from the gold-price sibling, but there is no explicit guidance on when-not-to-use or prerequisites.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
- Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the tool returns an emoji and mood score, and mentions cost (3 sats) and category. However, it does not describe any side effects, rate limits, or behavior on empty input. The description is adequate but not highly detailed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively concise, front-loading the core purpose. However, it redundantly includes the parameter info both in text and as a separate line. It could be slightly streamlined, but overall it's efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has a single parameter (wrapped in JSON) and an output schema exists, the description covers the main functionality. However, it does not mention the mood score range or any text length limits, leaving some gaps. It is adequate for a simple tool but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has a single 'params' parameter with no description (0% coverage). The description compensates by stating that the JSON string must contain a 'text' field (required) and explains its purpose: 'Text to analyze for emoji sentiment.' This adds significant meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Analyze text and return the emoji that best matches the vibe, plus a mood score.' It specifies the resource (text) and the output (emoji and score), and distinguishes it from siblings like d3p_vibe-check by focusing on emoji sentiment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives examples of when to use ('tweets, DMs, commit messages') but does not provide explicit guidance on when not to use it or how it differs from alternatives like d3p_vibe-check or d3p_roast-my-idea. The usage context is implied but not clearly bounded.
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 bears full burden. It indicates a read-only 'check' operation but does not disclose idempotency, rate limits, or polling behavior. Minimal behavioral detail beyond basic safety.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: one for purpose and one for the parameter. Front-loaded and free of unnecessary words, making it highly scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists (though not shown), the description needn't detail return values. It provides the essential info: purpose and parameter source. Minor gap: no mention of how to interpret status in response, but output schema likely covers that.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so description compensates by explaining pipeline_id as 'the ID returned by d3p_pipeline_execute,' adding critical context about where the value comes from that the schema alone lacks.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Check the status of a running pipeline execution,' specifying the action (check status) and resource (pipeline execution). Among siblings like d3p_pipeline_execute and d3p_pipeline_result, this tool's purpose is distinct and unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after d3p_pipeline_execute by referencing the pipeline_id from that tool. However, it lacks explicit guidance on when not to use it (e.g., for final result) or mention of alternatives like d3p_pipeline_result.
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 provided, so description must cover behavior. It mentions returning validity and error details, but does not disclose permissions, rate limits, or whether the operation is read-only. Adequate but not thorough.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness3/5Is the description appropriately sized, front-loaded, and free of redundancy?
Includes extra metadata like 'Category: code | Cost: 5 sats | Endpoint: validate-schema', which is unnecessary for agent usage. The description is not overly long, but could be more concise.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present, the description need not detail return format. It states returns 'validity status and error details', which is sufficient. The parameter description is adequate for a simple validation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only shows a single 'params' string, but the description explains that it should contain 'payload' and 'schema' objects as JSON. This adds critical meaning beyond the schema, compensating for 0% schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool validates a JSON payload against a schema and returns validity status and error details. It is distinct from siblings, none of which perform schema validation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use vs. alternatives or prerequisites. The tool is self-explanatory for validation tasks, but lacks exclusions or context for when not to use.
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 disclose behavioral traits. It indicates a read-only check operation (no side effects), but does not mention what happens if parameters are missing or invalid, nor does it specify any prerequisites or rate limits. The 'check' verb implies non-destructiveness, but more detail could improve certainty.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences that clearly state purpose and parameter details. No redundant information; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (not shown), description does not need to detail return values. It covers the tool's function and parameter structure. However, it could mention the expected output type (e.g., boolean) for extra clarity. Overall adequate for a simple check tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema (only 'params' string) is generic with 0% schema coverage. The description compensates by specifying the JSON structure with 'source_service' and 'target_service' as required fields, adding critical meaning beyond the bare schema. However, it does not document allowable values or formats for these fields.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: checking compatibility between two d3p services for chaining. It uses specific verbs ('Check if... can be chained') and identifies the resource (d3p services). It distinguishes from siblings like d3p_validate-schema by focusing on cross-service compatibility.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when chaining services, but it does not explicitly state when to use this tool versus alternatives like d3p_validate-schema or d3p_protocol_info. No when-not-to-use instructions 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 cover behavioral traits. It correctly implies a read-only operation but does not mention error conditions (e.g., incomplete pipeline) or other side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences front-load the purpose and immediately follow with parameter details; no extraneous information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the output schema exists and the tool has only one parameter, the description is sufficient for basic usage. It does not elaborate on prerequisites or error handling, but these are less critical for a simple retrieval tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema description coverage, the description adds valuable context by explaining that pipeline_id is the ID from d3p_pipeline_execute, helping the agent locate the correct input.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description uses specific verb 'Get' and resource 'final result of a completed pipeline', clearly distinguishing it from siblings like d3p_pipeline_status which provide status updates.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage after pipeline completion and specifies the parameter source, but does not explicitly contrast with d3p_pipeline_status or mention 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?
No annotations are provided, so the description carries the full burden. It implies a read-only search operation but does not explicitly state side effects (e.g., no destructive actions). The description is adequate but not explicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Description is front-loaded with a clear sentence followed by a parameter list. It is concise but the parameter list could be more structured. No wasted sentences.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity and the minimal input schema, the description provides necessary details for the input. An output schema exists (not shown) so return value description is not required. Complete for agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema coverage at 0%, the description fully compensates by detailing the JSON parameters expected inside the 'query' string, including types and examples. The bare schema only shows 'query' as a string without any guidance.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the tool is for 'Search for d3p services by capability, price, reputation, or latency' which is a specific verb+resource combination. It distinguishes from siblings like d3p_list_services by implying it's a filtered search.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
Description explains that all filter fields are optional and that an empty query returns all active services, giving context for usage. However, it does not explicitly mention alternatives or 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?
No annotations are provided, so the description carries full burden. It adds context like 'Cost: 5 sats' and 'Endpoint: eli5', but does not discuss idempotency, error handling, or permissions. It gives moderate insight into behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two paragraphs plus parameter info. It is well-structured and informative, but includes extra details like cost and endpoint that could be considered verbose. Still, every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With an output schema present (not shown), the description doesn't need to explain return values. The purpose, usage, and parameter semantics are well covered. It feels complete for a straightforward text transformation tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only shows a single 'params' string with default '{}' and no description (0% coverage). The description compensates fully by explaining that the JSON string should contain a 'text' field (required) and what it expects ('Complex text to simplify'). This adds essential meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Explain Like I'm Five. Paste in jargon-heavy text and get back a version a kindergartner could understand.' It uses specific verbs (simplify, swap) and resources (technical terms). This distinguishes it from siblings like d3p_vibe-check or d3p_error-translator, which have different functions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives a usage hint: 'Chains great after search or code analysis.' This implies when to use it. However, it does not explicitly state when not to use or mention alternatives, though no direct competing sibling exists.
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?
No annotations are provided, so the description bears full responsibility. It discloses that the tool validates syntax, returns formatted output with stats, and provides error location with fix suggestions. This clearly indicates it is a read-only operation, uses validation, and imposes a 50KB size limit. No contradictions.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is relatively concise but includes extraneous details like 'Category: code | Cost: 3 sats | Endpoint: json-formatter' in a line break format. The core description is front-loaded and clear, but the additional metadata could be integrated or omitted to improve conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's moderate complexity and the presence of an output schema, the description is complete. It explains the return value (formatted output with depth/key stats or error location with fix suggestions) and the input constraints (max 50KB). No further details are necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has one 'params' string parameter with 0% description coverage. However, the description explicitly documents the expected JSON string parameter (json_string, required, max 50KB), adding significant meaning beyond the schema. It compensates well for the lack of schema annotations.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'Pretty-print messy or minified JSON with syntax validation' and specifies the output includes depth/key stats or error location with fix suggestions. This is a specific verb ('pretty-print') and resource ('JSON'), and it distinguishes from sibling tools which cover different domains.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for formatting/validating JSON with a 50KB limit but does not explicitly state when to use versus alternatives or when not to use it. No sibling differentiation is provided beyond the tool's own purpose.
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 full burden. It mentions 'atomic payments' and parameter details but lacks information on side effects, required permissions, or asynchronous behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
Well-structured with a purpose sentence, parameter breakdown, and example. Slightly verbose but the detail is justified due to the complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Parameters and example are well-covered, but lacks description of output, error handling, or whether execution is synchronous. An output schema exists but is not referenced.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% (only a string 'pipeline'), but the description fully explains the internal JSON structure (steps, pipeline_input, max_total_sats, timeout_seconds) and provides an example, adding high value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it 'execute a multi-service pipeline' with chaining, schema mapping, and atomic payments. It distinguishes from sibling tools like d3p_pipeline_status or d3p_pipeline_validate, which handle other pipeline lifecycle stages.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use (to run a pipeline) and the sibling names provide context, but it does not explicitly state when not to use or recommend alternatives.
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?
No annotations are provided, so the description carries full burden. It correctly notes the tool's cost (5 sats) and category, and clarifies the input format (pass as JSON string). It does not mention destructive actions or authentication needs, which is appropriate for a simple fun tool. The description is transparent about the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is succinct and well-organized: a one-line summary, followed by metadata (Category, Cost, Endpoint), then parameter details. It is front-loaded with the main purpose and uses clear formatting, making it easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the presence of an output schema (indicated by context signals), the description does not need to explain return values. It covers necessary input requirements and usage. A minor gap is the lack of mention of output format examples, but overall it is complete for this simple tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema only has a generic 'params' string with 0% schema coverage. The description adds critical meaning by detailing that the JSON string must contain 'characteristics' and 'color' with examples. This fully compensates for the schema's lack of structure, ensuring correct parameter usage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Generate creative cat names based on physical characteristics and color', using a specific verb ('Generate') and resource ('cat names'). It distinguishes from sibling tools like 'd3p_roast-my-idea' (roasting ideas) and 'd3p_shitpost' (generating shitposts) which serve different purposes.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description lists required inputs (characteristics and color) but does not explicitly state when to use this tool versus alternatives. Usage context is implied through the 'Category: fun' tag, but no when-not-to-use 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.
- 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 the read-only nature via 'List' and provides context with examples. However, it does not elaborate on behavior like authentication or 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.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence with examples, immediately conveying the purpose with no extraneous words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the lack of parameters and presence of an output schema, the description fully characterizes the tool's functionality. The examples enhance understanding.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
There are no parameters, so the schema coverage is complete. The description adds no additional parameter info, but the baseline for zero parameters is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists pre-built pipeline templates, with specific examples like 'research' and 'market_intel'. This distinguishes it from siblings like d3p_pipeline_execute and d3p_pipeline_status.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage when one needs to see available templates, but it does not explicitly state when to use this tool vs alternatives, nor does it provide any conditions 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?
No annotations are provided, so the description carries the full burden. It discloses the output (one-paragraph roast), detection of common tropes, cost (5 sats), and endpoint. It is transparent about the behavior, though it does not detail any limitations or side effects, which are minimal for a text tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise (2-3 sentences) with a natural, engaging tone. It includes all essential information without redundancy. A slightly more structured format could improve scanability, but it is efficient and front-loaded with the core action.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity and the presence of an output schema (not shown), the description is complete. It covers the input, the process, the output characteristics, and even extra flavor ('Cheaper than a bad cofounder'). No critical information is missing for an AI agent to use this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters5/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 0% description coverage, so the description must compensate. It clearly explains the required parameter 'idea' as a string, specifies the format (JSON string), and provides context ('Your startup idea to be roasted'). This fully compensates for the schema's lack of descriptions.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: 'Submit your startup idea and receive a brutally honest one-paragraph roast.' It specifies the resource (startup idea) and the output (roast), and distinguishes from siblings like d3p_vibe-check by its humorous tone and focus on roasting.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use – when you want a roast of a startup idea – but does not explicitly mention when not to use or provide alternatives. The fun tone suggests it's not for serious analysis, but no direct guidance on alternatives like d3p_vibe-check or d3p_shitpost.
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?
Without annotations, the description carries full burden. It discloses cost (3 sats), endpoint, and parameter details. It implies a read-only calculation, but does not detail side effects or output structure. Overall transparent given tool simplicity.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is very concise: two sentences plus compact metadata. It front-loads the purpose and provides parameter details efficiently. No unnecessary content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple calculator with an output schema, the description covers the essential inputs and purpose. It could mention that reset_time should be a future timestamp, but it is largely complete and sufficient for the tool's complexity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema only has a generic 'params' string with 0% coverage. The description compensates by specifying expected JSON fields (remaining, reset_time) and their types, adding crucial meaning beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states 'Calculate wait time and strategy for rate-limited API calls', which is a specific verb and resource. It distinguishes itself from sibling tools which are unrelated (e.g., weather, shitpost, etc.).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implicitly tells when to use the tool: when needing to calculate wait time for rate-limited API calls. No exclusions are needed since siblings are not competitors, but explicit 'when to use' guidance is missing.
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 full burden. It states the tool lists services—a read-only operation—but does not explicitly confirm it is non-destructive or mention any authentication needs. However, for a simple listing with no parameters, the description is sufficiently transparent about its behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loading the action and content. Every word contributes meaning; there is no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given zero parameters and an output schema presumably documenting the return structure, the description is fully complete. It tells the agent what the tool returns (services with pricing, categories, descriptions) and when to call it (first). No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters and schema coverage is 100%, so the description does not need to add parameter information. The baseline for 0 parameters is 4, and no further detail is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'List all available d3p services with their pricing, categories, and descriptions,' which uses a clear verb (list) and resource (d3p services) and specifies what details are included. This clearly distinguishes it from sibling tools that perform other operations on services.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly says 'Call this first to see what's available,' providing a clear recommendation for when to use the tool. No alternatives are needed as this is the primary listing tool.
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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