Marketing Skills Directory

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description carries the full burden. It does add real value by disclosing exactly which fields are returned (pricing, free tier, auth, data provided, docs/pricing URLs, endpoints, editor note). However, it says nothing about read-only behavior, what happens when a slug is unknown, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with the verb and scope first, followed by the return-field list; every clause earns its place and there is no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema and no annotations, enumerating the return fields is exactly what's needed to make the tool callable with confidence. Only minor gaps remain (lookup-failure behavior, read-only nature).

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There is one parameter at 100% schema description coverage, so the schema already defines 'slug'. The description only echoes 'by slug' without adding format guidance (e.g., where slugs come from, case sensitivity), so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Return the full public listing for an API by slug') and enumerates the returned fields, so the agent knows exactly what it retrieves. It doesn't name the sibling it complements (search_apis), but 'by slug' plus 'full listing' implicitly contrasts with a search operation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than stated: requiring a slug signals this is a follow-up detail fetch after search_apis, but the description never says when to use this versus search_apis or get_set/list_categories. No exclusions or prerequisites are given.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must cover behavior. It only says 'return' without discussing side effects, permissions, or data scope. Inadequate for a non-annotated tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence with no filler. Front-loaded purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema, so description should hint at return structure. 'Full details' is vague; could specify what details are included.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema covers 100% of parameter meaning (slug with example). Description adds no extra semantics beyond schema, meeting baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns a skill set with full details for each skill, distinguishing it from siblings like get_skill or list_sets.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied but no explicit guidance on when to use or alternatives. Agent might infer from context but lacks clear direction.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description discloses key behaviors: free vs. premium content handling and the role of the access code. However, it omits error cases (e.g., invalid slug) and any 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.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences with no extraneous detail. The first sentence states the primary action, the second adds critical nuance, making it front-loaded and efficient.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 params, no output schema), the description covers the essential behavior. It is missing some details like error handling, but is reasonably complete for its complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so baseline is 3. The description adds meaning beyond the schema by explaining the dual behavior for premium skills, which clarifies the purpose of the 'code' parameter.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description specifies a clear verb ('Return') and resource ('full SKILL.md content'), and distinguishes behavior for free vs. premium skills, differentiating it from sibling tools like list_skills.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (to get full content for a specific skill) but does not explicitly mention alternatives or when not to use it. Sibling names are provided but no direct comparison is made.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It accurately describes the behavior: listing all categories with counts. It does not mention any side effects or special requirements, but for a simple read-only list tool, this is sufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, well-structured sentence that provides all necessary information without any waste. It is concise and front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has no parameters and no output schema, the description is mostly complete. It mentions the output includes counts, but does not specify the exact structure or format. For a straightforward listing, this is acceptable.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters, and the baseline is 4. The description adds value beyond the empty schema by specifying that the output includes counts, which is meaningful for an agent deciding to invoke this tool.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists all skill categories with counts and explicitly identifies it as the filter vocabulary for list_skills, which distinguishes it from sibling tools like list_skills and search_skills.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage as a preparatory step before list_skills by stating it provides the filter vocabulary. Although it does not explicitly state when not to use it, the context signals and sibling tool names make the intended use clear.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided. Description only says it lists sets with skill slugs, missing behavioral details like read-only nature, auth requirements, or pagination.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

One sentence, 8 words. Very concise but earns its place. Could add more context without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Adequate for a parameterless list tool but missing details about scope (all sets? filtered?), output format, or whether it returns all sets.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has zero parameters with 100% coverage, so baseline is 4. Description adds context that output includes skill slugs, which is not in schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it lists curated skill sets (bundles) with their skill slugs, which is a specific verb+resource and distinguishes from siblings like list_skills or get_set.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool vs alternatives (e.g., get_set for a single set). No context about use cases or limitations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so the description must convey behavior. It mentions pagination indirectly via 'limit' and 'offset', but does not disclose ordering, response structure, or effects. Minimal transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very short (one sentence), which is concise but lacks important details like return values and pagination clues. It is not front-loaded with critical info.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and only 33% parameter description coverage, the description fails to specify return structure or pagination behavior. It is incomplete for a tool with 3 parameters and optional filtering.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is only 33% (category described). The description adds no detail beyond the schema for 'limit' and 'offset', and 'category' is only repeated. Does not compensate for low coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: browsing the skills catalog with optional category filtering and pagination. It distinguishes from siblings like 'list_categories' (lists categories) and 'search_skills' (likely search).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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 mention of 'optionally filtered by category' implies usage, but no when-not or context for pagination.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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 that the tool returns top 3 matching skills with exact install commands, which is behaviorally transparent. It could mention lack of side effects or authorization needs, but the core behavior is clear.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single concise sentence that wastes no words. It is front-loaded with the core purpose and output details.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description adequately explains the return structure (top 3 matching skills with install commands). It provides sufficient context for a simple one-parameter tool, though it could mention edge cases like no matches found.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already provides 100% coverage with a clear description and example for the only parameter 'task'. The tool description does not add significant semantics beyond what the schema offers, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'recommend' and resource 'skills', and specifies the output format as top 3 matching skills with install commands. This distinguishes it from sibling tools like list_skills (lists all) and search_skills (search by name).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use when you have a natural-language task and need relevant skills. However, it does not explicitly state when not to use this tool or name alternative tools for different scenarios.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden. It does well on the return surface ('Returns pricing model, price, free tier and auth type') and on matching behavior ('case-insensitive match over title, excerpt and data provided'), which substitutes for the missing output schema. However it says nothing about result ordering, the limit/pagination contract, or whether all matches are returned — meaningful gaps for an unannotated tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, zero filler, correctly front-loaded: purpose first, then match semantics, then return shape. Every clause carries information the agent needs.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 4-parameter read tool with no annotations and no output schema, the description covers the critical unknowns: what is searched, how matching works, and what fields come back. The remaining gap is the limit/pagination contract and how results are ordered, which leaves it slightly short of fully self-sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 50%: query and category are documented, limit and pricing_model are not. The description partially compensates by explaining that the query matches across title, excerpt and data provided (case-insensitively), which is real added meaning beyond the schema's bare example. It adds nothing for limit, and pricing_model is left to a self-explanatory enum.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Uses a specific verb+resource ('Search third-party data APIs ... listed in the directory') and names the matched fields and domain (SEO, analytics, enrichment). It implicitly contrasts with get_api/list_categories through the word 'search', but never names a sibling explicitly, so differentiation is inferred rather than stated.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is only implied: 'search' suggests exploration when the specific API slug is unknown, versus get_api for a known record. There is no explicit when-to-use/when-not statement, no guidance on empty results, and no pointer to alternatives; only the inline '(see list_categories)' hint for the category parameter.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Describes the search algorithm (BM25) and ranked results, but no annotations exist. Lacks disclosure of read-only nature, authentication needs, or rate limits. Adequate but not fully transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences only, direct, no filler. Efficiently communicates core functionality.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers search method, ranking, and output fields. With no output schema, description provides necessary output details. Minor omission: no mention of pagination or default limit, though schema defines limit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema has 50% coverage (only query has description with example). Tool description adds no additional parameter context beyond schema. Limit parameter remains undocumented in both.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it performs full-text (BM25) search over the skills directory, with explicit output fields (slug, title, description, categories, price). Distinguishes from sibling tools like list_skills (lists all) and recommend_skill (recommends based on criteria).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does 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 (e.g., list_skills, recommend_skill). No preconditions or exclusions mentioned.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.