authority.md

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

With no annotations provided, the description carries the full behavioral burden. It discloses the return payload (metadata, a 'type' field, a content preview) and calls out the special bundle branch (returns the full persona-slug list needed for purchase_persona), which is genuinely beyond-schema behavioral context. It does not cover error behavior or explicitly disclaim side effects, but the 'Get/Returns' framing clearly signals a read-only operation.

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?

Four sentences, each earning its place: purpose, workflow placement, return summary, and slug types plus bundle behavior. The most decision-critical information (purpose and when to use) is front-loaded. It is dense rather than 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?

No output schema exists, so the description rightly summarizes return values and the bundle-specific behavior. For a one-parameter read tool, it covers purpose, usage timing, parameter values, and output shape. Only minor gaps remain (e.g., behavior on invalid/unknown slugs), which are low-severity for this 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?

Schema coverage is 100%, so the baseline is 3. The description largely restates what the schema already documents (slug types with examples) and adds only the bundle-specific output context. A minor term mismatch exists — the schema calls the middle category a 'skill slug' while the description calls it a 'Tool slug' — which slightly reduces the value the description adds.

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 uses a specific verb-resource pair ('Get the full details for a specific product on authority.md'), concretely enumerates the three product types (persona framework, functional Tool, curated Bundle), and differentiates from siblings by positioning itself relative to search_personas and purchase_persona. An agent can tell exactly what this tool does and how it differs from its 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?

The description explicitly states when to use the tool ('Use after search_personas to show complete information before purchase') and connects to purchase_persona by noting bundles return the persona slugs needed for that call. It gives clear workflow placement, though it never explicitly says when NOT to use it in favor of an alternative.

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 burden. It states this is a listing operation that returns all categories from authority.md, implying a safe read with no side effects. It does not describe the output shape or ordering, but for a simple category list this is a minor gap.

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, with the core action front-loaded and the usage guidance immediately after. No filler or repeated schema content.

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, the description gives enough context to choose and invoke it correctly. The only thing absent is an explicit statement of the return format (e.g., an array of category names), which is not critical for such a simple operation.

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 no parameters, and the schema is an empty object with 100% coverage, so the baseline of 4 applies. There is nothing for the description to add.

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 uses a specific verb ('List') and resource ('all categories of thinkers available on authority.md'), with concrete examples (Investor, Tech Visionary, Philosopher). It clearly distinguishes the tool from name-based search, its main sibling.

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 an explicit use condition: when the user wants to browse by domain rather than search by name. Though it does not name search_personas directly, 'search by name' unambiguously identifies the alternative path.

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 and does so thoroughly. It discloses that the tool returns a URL, that checkout is hosted by authority.md and processes payment via Stripe, that bundles require all 10 persona slugs, that mixed carts are allowed, the 1-50 slug limit, and the requirement to confirm with the user first. This is rich behavioral disclosure.

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 dense and packed with necessary information, well front-loaded with the core purpose. While it is long, every sentence adds operational value and the structure flows logically from what the tool does, to inputs, to special cases, to return value, to prerequisites.

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?

The tool has one parameter, no output schema, and no annotations, yet the description covers everything needed for correct usage: input constraints, bundle purchasing procedure, pricing lookup references, return behavior, and a mandatory confirmation step. Nothing critical is missing.

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?

Despite 0% schema description coverage, the description adds substantial meaning to the single 'slugs' parameter: it defines what slugs can be (personas and/or Tools), explains mixed carts, specifies bundle handling (10 persona slugs from get_persona_details), and notes pricing tier implications. This far exceeds the minimal schema of an array of strings.

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 opens with a specific verb and resource: 'Generate a checkout URL on authority.md for purchasing one or more frameworks, Tools, or Bundles.' This clearly distinguishes purchase_persona from its siblings (get_persona_details, list_categories, search_personas), which are all read/search operations.

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 context on when to use this tool ('Confirm with the user which items they want... BEFORE calling') and directs users to get_persona_details for prices and bundle slugs. It names the alternative for retrieving pricing data but does not explicitly state when NOT to use this tool versus alternatives.

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 provided, the description carries the full behavioral burden. It discloses the result shape ('type' field, slug, focus, and price) and even points to the external source for current prices, giving agents a realistic picture of what a successful call returns.

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 sentences and front-loads the core action plus marketplace context. The examples and price details are mildly verbose but earn their place because they clarify the type taxonomy and the external pricing caveat.

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 compensates by describing result fields and the pricing data source. It gives enough context for an agent to invoke the tool correctly, though it does not describe ordering, empty-result behavior, or when to prefer get_persona_details.

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 75%, so the schema already documents query, type, and category. The description adds semantic depth by explaining what each product type means, how the type filter values map to marketplace concepts, and what fields like focus and slug represent.

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 opens with the concrete action 'Search the authority.md marketplace' and then clarifies what lives there by naming the three product types with examples. This clearly distinguishes search_personas from the sibling tools that fetch details, list categories, or purchase.

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 explicitly says to use the tool when the user asks about a specific person, category, task, or recommendation. It does not explicitly state when not to use it or name alternative sibling tools, but the usage context it provides is clear and actionable.

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