PostLaunchKit Directory

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

With no annotations the description carries the full burden, and it does disclose one non-obvious behavioral trait: only 'published' entries are returned, so unpublished slugs presumably fail. It says nothing about not-found behavior, permissions, or return shape, so it is only partially 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?

A single front-loaded sentence with the resource and the lookup key; every word earns its place and nothing is padded.

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 trivial one-param read tool with no output schema this is close to adequate, but the 'published' restriction raises an unanswered question about what happens for unpublished or missing slugs, which an agent calling this tool will need to handle.

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?

One parameter at 0% schema description coverage; the schema only says it is a string. The description adds that the slug is the lookup key for a published entry, which is real semantic value, but gives no format, casing, or uniqueness details.

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 (get) and resource (one published directory entry) and narrows it with 'by its slug,' which separates it from list_categories and search_projects. It never explicitly names those siblings, but the single-item-by-key framing is unambiguous.

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 when-to-use guidance and no comparison to alternatives such as search_projects for lookup by other criteria. The only implied usage is 'you already have a slug,' which the agent must infer.

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 does disclose one meaningful behavioral trait — the counts cover only published entries, not all entries — which is genuine added context. However, it says nothing about pagination, result ordering, or whether the operation is a safe read.

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 verb front-loaded and the most informative qualifier (published-entry counts) immediately after. Nothing is wasted and nothing 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 read-only listing with no output schema, the description covers what the tool returns (categories plus per-category counts) and the count scope. The only minor gap is the shape/ordering of the returned list, which is low-stakes here.

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 the baseline of 4 applies. No additional parameter meaning is needed or expected.

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 directory categories') and adds scope detail ('with the number of published entries in each'), so the agent knows exactly what comes back. It does not explicitly differentiate itself from the sibling project tools, but those operate on a different resource, so confusion is unlikely.

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 explicit when-to-use or when-not-to-use statement, and no alternative is named. Usage is only implied by the verb 'List' and the fact that none of the siblings (get_project, search_projects, submit_project) cover categories, so the agent can infer this is the sole category-enumeration 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 real work: it discloses row contents, warns that 'Provider claims are not independently observed listing links,' and states that 'Blank/unknown stays unknown' rather than being inferred. It omits return shape, result volume, and pagination behavior for a 10-param listing 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?

Purpose and dataset are front-loaded in the first sentence, and the subsequent sentences are substantive caveats rather than filler. It is slightly dense and run-on (mixing row content, evidence caveats, and workflow advice), but almost every clause earns its place.

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 10-parameter tool with no output schema and no annotations, the description covers data caveats and one recommended filter but leaves much of the filtering surface and the return shape unexplained. It is adequate to call the tool, but not complete enough to predict results.

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 40% across 10 params, so the description must compensate, and it partially does: it explains checked=true ('source-backed eligibility and free-tier options; not guaranteed approval') and the reliability semantics behind link_evidence values such as provider_claim and unknown. However, eight other filters (query, free, dofollow, link_type, product_type, requires_account, ai_agent_friendly, badge_requirement) get no clarification beyond their names/enums.

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 directories and listing sites where an indie product can be submitted') plus the data provenance (open launch-directories dataset, CC BY 4.0). The resource is narrow enough to separate it from siblings like list_categories or search_projects, and it names run_launch_check as a companion step.

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?

Gives concrete usage guidance: 'Use checked=true for source-backed options' and 'Run run_launch_check on the product site before submitting,' which places it in a workflow. It lacks any when-not-to-use guidance or explicit contrast with the other list/search siblings, so it stops short of a 5.

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 well: it discloses the return shape (passed/total counts, per-check status with a fix for failures, a report link) and a concrete rate limit of 20 checks per IP per day. It omits auth requirements and whether the check is idempotent or how long it takes, keeping it short of 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?

Three tight sentences, front-loaded with the action and target, then the return contents, then the hard limits. No filler and every clause carries information.

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, the description compensates by explaining what is returned and the rate cap. It is essentially complete for a single-parameter read-style tool, though an agent would still benefit from knowing about auth or timeout behavior.

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?

Only one parameter exists and the schema already documents it at 100% coverage, so the baseline is 3. The description adds real constraint value by restricting the URL to public sites, which the schema's 'Public website to check' phrasing only weakly conveys.

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 (run the PostLaunchKit launch check) on a clearly scoped target (a public website), which no sibling tool overlaps with. An agent can identify this as the site-auditing tool without opening the 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?

The description constrains usage with 'Public sites only' and gives a rate limit, which implies the appropriate context. However, it never states when to prefer this tool or what to do for non-public/authenticated targets, leaving usage guidance implicit.

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 exist, so the description carries the full burden. It usefully discloses that entries are human-reviewed and that unpublished entries are filtered out, but says nothing about pagination behavior, result limits, ordering, or return shape — meaningful gaps for a search endpoint.

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, front-loaded with the core action and resource, followed immediately by the scope constraint. No filler or repetition.

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 four loosely documented optional parameters, no output schema, and no annotations, the description is too thin. It omits pagination semantics, result limits, and how the tag/query/category filters combine.

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 25%: three of four parameters (tag, page, category) carry no schema description, and the description mentions no parameter at all. It neither explains how tag/query/category interact nor how pagination works, so it fails to compensate for the coverage gap.

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 ('Search') and resource ('PostLaunchKit directory of human-reviewed free tools and projects'), plus a scope refinement ('including AI agent tooling'). An agent can distinguish this from get_project/list_categories/submit_project, though no sibling is named explicitly.

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: search when you need to discover entries, use get_project when you have one. The description never states when to prefer it over its siblings or when not to use it. Only the 'published entries only' constraint hints at scope.

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 behavioral burden. It usefully discloses that submissions are saved as pending and human-reviewed with nothing published automatically, but it omits permissions, duplicate handling, error behavior, and any post-submission editing or withdrawal process.

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 short sentences with no filler, and the core action is front-loaded before the review-process caveat. Every sentence contributes directly to understanding the submission workflow.

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 an eight-parameter submission tool with no annotations, low schema coverage, and no output schema, the description is too thin. It covers only the pending-review behavior and leaves an agent without guidance on required inputs, constraints, or expected outcomes.

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 only 38%, with five required parameters and eight total parameters, yet the description adds no parameter-level meaning at all. It does not clarify fields such as name, one_liner, category, tags, or agent_name that the schema leaves undescribed.

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 action and resource: suggest a product for the directory. It implicitly contrasts with read-oriented siblings such as get_project, list_categories, and search_projects, though it does not explicitly name an alternative or scope constraint.

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 gives no when-to-use guidance, no prerequisites, and no routing advice versus the sibling read tools. It explains what happens after submission, but not when an agent should choose this tool over browsing or searching the directory.

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