TheSkillVault

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's job is to add return-shape context, which it does: ordered steps with skill name, inputs/outputs, and links. Minor gaps remain around behavior for unknown bundle ids and whether any bundle-level metadata beyond steps is included.

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 tight sentences: the first front-loads what is returned and the shape of each step, the second handles the hand-off to get_skill. No filler, nothing redundant with the schema.

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 one-parameter read tool with no output schema, the description covers the return shape and the sibling hand-off well. It stops short of noting edge behavior (invalid/unknown id) or any bundle-level fields, which keeps it just below fully complete.

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% and the single id parameter is documented with a max length and an example ('standard-website' from list_bundles), so the schema carries the load. The description adds nothing about the id format or constraints beyond what the schema already states — baseline 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?

Specific verb and resource ('Returns one bundle's ordered steps') plus a precise description of the payload: skill name, inputs/outputs per step, and web link. It also differentiates itself from get_skill by stating that full step instructions live there, so an agent can distinguish the two without opening a schema.

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?

'Full instructions for a step come from get_skill' explicitly routes the agent to the sibling for deeper detail, and the schema notes the id comes from list_bundles. However, there is no statement of when this tool is preferable to alternatives (e.g., list_skills or search_skills) or any exclusion condition.

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 says 'Load the full' content, implying a potentially large read, but discloses nothing about failure on a non-exact name, size of the returned payload, or read-only safety. Bare minimum context 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?

One sentence, front-loaded with the verb and the payload being returned, with no wasted clauses. The exact-name constraint and the pointer to search_skills are both essential and compressed.

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 one-parameter read with a fully documented schema and no output schema, the description covers the core intent. Still missing is the get_skill vs get_skill_file distinction and any hint about what 'full SKILL.md' returns, which matters on a crowded sibling set.

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% and the name parameter already documents 'Exact skill name, e.g. deploy-nextjs-to-vercel'. The description reinforces exactness and its provenance (from search_skills), but adds no format or matching details beyond the 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?

States a specific verb (Load) and resource (full SKILL.md instructions) scoped to one skill by exact name. Distinguishes itself implicitly from get_skill_file (one file within a skill) and from list/search siblings, though it doesn't explicitly name the boundary with get_skill_file.

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?

Points the agent to search_skills as the source of the name, which implies use-after-search. However, it never states when to use get_skill vs get_skill_file, the closest and most confusable sibling, leaving that routing decision to inference.

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. 'Load' implies a read-only fetch and the relative-path scoping constraint is useful, but nothing is said about what happens on a bad path or unknown skill name, nor what the response contains (file text vs. metadata).

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, with the core action front-loaded and the dependency on get_skill second.

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 exists, so the description should indicate what the tool returns (raw file contents, truncation, encoding). It covers the call mechanics adequately but leaves the return shape unknown for a tool whose entire purpose is retrieving content.

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 description coverage is 100% and both parameters are already documented ('Exact skill name', 'Path relative to the skill folder, e.g. references/env-vars.md'). The description's example duplicates the schema rather than adding format or constraint detail beyond it.

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 ('Load one supporting file ... from a skill folder') and gives a concrete example path, which distinguishes it clearly from the sibling get_skill that lists files rather than fetching one.

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?

Explicitly routes the agent through get_skill's file list to obtain a valid path, which is real sequencing guidance. It does not state exclusions or what to do if the file is missing, but the usage context is 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?

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so safety is fully covered and the description need not restate it. The description adds value the annotations cannot: it enumerates the returned fields (id, title, audience, number of steps), which matters because there is no output schema. It does not address ordering or empty-result behavior, keeping it from a 5.

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 sentence with the resource name first and the concept definition immediately after, followed by the returned fields. Every clause earns its place — nothing is repeated from the title or annotations.

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 zero-parameter, read-only list tool with rich annotations and no output schema, the description covers purpose, the domain concept, and the return shape — everything an agent needs to select and call it. Only result ordering and the empty-list case are unaddressed, which is minor at this 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?

The tool takes zero parameters, so per the baseline this starts at 4. The description does not invent pseudo-parameters or filtering options that don't exist, which would have been misleading.

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 (Lists) and resource (skill bundles) and goes further by defining what a bundle actually is: 'ordered paths where each skill's output is the next skill's input.' That definition lets an agent distinguish bundles from skills without opening sibling schemas. It stops short of explicitly naming get_bundle or list_skills as the alternative, so a 4 rather than 5.

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 by the verb 'Lists' — the agent can infer this is the enumeration entry point and that get_bundle retrieves a single one. There is no explicit when-to-use or when-not statement, and no mention of whether any filtering is possible (none is, given zero parameters).

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 disclosure burden. 'List' implies a read, but it says nothing about whether results are paginated, whether counts are totals per category, or whether any permission is needed. 'With counts' is the only behavioral hint.

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 six-word sentence with the resource and the extra payload ('counts') front-loaded. Nothing is wasted and nothing important is buried.

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 zero-parameter listing tool with no output schema and no annotations, the description conveys the essential behavior. The remaining gap is what the counts represent and the shape of the response, but the scope is small enough that this is minor.

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 tool takes zero parameters, so the schema has nothing to document and there is no parameter ambiguity to resolve. Baseline 4 applies for a parameterless 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?

States a specific verb ('List') and resource ('skill categories') plus the notable detail that counts are included. It is distinguishable from list_skills/search_skills by the word 'categories', though the description never explicitly contrasts itself with those siblings.

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?

There is no guidance on when to use this versus list_skills or search_skills, and no stated preconditions. The agent must infer that this is the discovery/overview entry point before drilling into skills.

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?

While annotations define the safety profile (read-only, idempotent), the description adds crucial behavioral context by defining how the count is calculated: it includes skills written specifically for the family AND skills written for any AI.

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 efficient and well-structured, addressing the core function, the filtering capabilities, and the counting methodology in a single, coherent statement.

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 that all input parameters are documented and all safety behaviors are defined via annotations, the description is complete. It adequately explains the resource structure and the metrics returned by the tool.

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?

Since the input schema has zero parameters and 100% coverage, the baseline score is 4. The description does add marginal semantic value by listing the possible filtering dimensions (id, name, vendor), even if they aren't implemented as input parameters.

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 explicitly identifies the resource ('AI model families') and the action ('Lists'). It clearly distinguishes this from the list of siblings by focusing on 'families' and defining the specific content of the listing.

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 provides clear usage context by detailing the attributes by which the listed families can be filtered (id, name, vendor). However, it does not explicitly state when this tool should be used versus a similar tool like 'list_skills'.

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 at all, the description carries the full burden, yet it only discloses the returned fields (name, category, description). It says nothing about pagination, result ordering, catalogue size, or that the call is read-only beyond the verb "List" — meaningful gaps for a list tool with a filterable catalogue.

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 returned shape in parentheses and the filtering options trailing it — no wasted words, nothing buried.

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?

There is no output schema, so stating the returned fields is valuable, and read-only listing needs little safety context. But the unexplained `proven` parameter and the absence of any hint about result volume or ordering leave the definition only minimally 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 67% and the description reinforces the two filter parameters (category, model family), but it completely omits the third parameter `proven`, whose semantics (works-on-5-models, 365-day window) are subtle even in the schema. Baseline 3 fits given a moderate coverage level with one notable omission.

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 ("List all skills") plus the fields returned, which cleanly separates it from get_skill. However it never names the sibling it competes with (search_skills), so the differentiation is only implicit from the verb.

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?

"Optionally filtered by category and/or AI model family" implies when the filters apply, but there is no statement of when to use this versus search_skills or list_categories, and no note that omitting the filters returns the full catalogue.

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 behavioral burden and does well by disclosing the limited return format: names plus one-line descriptions only. It also explains the follow-up workflow via get_skill, though it does not mention pagination, rate limits, or other operational details.

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 three compact sentences with the most important instruction front-loaded: call this before starting a task. Every sentence adds useful information about purpose, return scope, and next steps.

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?

There is no output schema, so the description appropriately explains that results are names plus one-line descriptions and that get_skill must be used for full instructions. Combined with the fully documented input schema, this is complete enough for correct invocation.

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 description coverage is 100%, so all six parameters, including enum filters for model and category, are already documented in the schema. The description does not add parameter-level semantics beyond what the schema provides, so the baseline of 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?

The description states a specific verb and resource: it searches TheSkillVault for vibe-coding skills and prompts. It also distinguishes itself from get_skill by explaining that search returns only names and one-line descriptions, while get_skill loads the full instructions.

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?

It gives explicit timing — call before starting coding, deployment, debugging, design, or prompt-writing tasks. It also names the alternative get_skill and the condition for using it: load the best match before doing the task.

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