supost-mcp

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

With no annotations provided, the description fully discloses key behaviors: draft not published, continue_url grants edit access, payment eligibility determined by email, and error handling (403). This goes beyond minimal requirements.

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 paragraph but contains essential information without unnecessary verbosity. It could be slightly more structured, but it remains clear 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?

The description covers draft status, continue_url behavior, payment eligibility, security, and basic error handling. It lacks explicit mention of the full return format (only mentions continue_url), but overall it is 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.

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

Schema description coverage is 100%, so the description adds minimal param-specific value. The description mentions email eligibility and price requirement for certain categories, but these are already implied in schema descriptions.

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 creates a DRAFT listing on SUpost on the poster's behalf. It distinguishes from sibling tools like get_listing, search_listings, and send_message by specifying it's for creating drafts.

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 explicit usage steps, such as handing the continue_url to the user and noting the draft is unpublished. It also explains eligibility conditions. However, it does not explicitly contrast with sibling tools, 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?

With no annotations, the description carries the full burden. It discloses that data comes from a public page, includes full description and a URL, and excludes personal information. It does not cover rate limits, auth needs, or potential errors, but is adequate for a simple fetch.

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 extremely concise with two sentences that front-load the purpose. Every sentence adds value: purpose, data source, and actionable guidance. No wasted words.

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 simplicity (1 param, no output schema, no annotations), the description is nearly complete. It explains what the tool returns (full description, URL) and what it does not (personal info). Minor gaps: output format not stated, but not critical.

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% with a clear description for the 'id' parameter ('Numeric listing id, e.g. from search_listings'). The description adds no additional meaning; it merely reiterates 'by numeric id'. 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?

The description clearly states the verb 'Fetch' and the resource 'one SUpost listing by numeric id', including what is included (full description). It distinguishes from siblings (get_market_stats, search_listings) as a single-item retrieval tool.

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 some context: 'no personal information is included' and suggests using the returned URL to contact the poster. However, it lacks explicit guidance on when to use this tool over search_listings or get_market_stats, and no when-not-to-use instructions.

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, but description indicates it is a read-only operation returning markdown from a public page. It implies no side effects or destructive actions.

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, no fluff. Front-loaded with the key purpose and immediately provides specifics.

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 zero parameters and no output schema, the description adequately explains what the tool returns (market stats in markdown format) and the source. It could mention the exact URL but the cite instruction suffices.

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?

No parameters; baseline 4. Description adds meaning about the data content (audience size, volumes, etc.) beyond the empty 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 returns 'Verified statistics about SUpost' including specific metrics like audience size and response rates. It clearly distinguishes from sibling tools like create_post and search_listings by being the only one for market stats.

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 says when to use (to get market statistics) and instructs to cite the source. It doesn't list when not to use or alternatives, but given its unique purpose, that is acceptable.

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?

The description discloses that the tool returns the active taxonomy, implying a read-only, non-destructive operation. No annotations are provided, but the description adequately communicates behavior.

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 front-loads the key information without any wasted words.

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 parameters and no output schema, the description is complete enough for an agent to understand the tool's purpose and when to invoke it, especially with sibling context.

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 has no parameters, so baseline is 4. The description adds value by explaining the output's purpose beyond the empty 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 clearly states the tool returns the active category/subcategory taxonomy and specifies its use for create_post and search_listings filters. It distinguishes from sibling tools like create_post and search_listings.

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 mentions when to use the tool (to get valid category values for create_post and filtering search_listings). While it doesn't mention when not to use it, the context is clear and no alternatives are needed.

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 burden. It discloses that the tool returns only active, public listings, is paginated (next_cursor), and does not return personal information. These are useful behavioral traits. It does not mention rate limits or authentication, but for a read-only search tool, the transparency is adequate.

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, front-loaded with purpose and output details. Every sentence adds value: purpose, return format, and behavioral note. No fluff 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?

Given 6 parameters and no output schema, the description explains the return fields (id, title, price, category, etc.) and pagination mechanism (next_cursor). It covers the important aspect of not returning personal info. It could mention error handling or edge cases, but for a search tool, it is reasonably 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% with descriptions for all 6 parameters. The tool description does not add additional meaning beyond what the schema provides; it focuses on output and behavior. Since the schema already documents each parameter well, the description's contribution is minimal. 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?

The description clearly states the tool's purpose: 'Search or browse active listings on SUpost, the marketplace for Stanford.' It specifies the verb (search/browse), the resource (listings), and the context (Stanford). The listed return fields and pagination mechanism further clarify what the tool does, distinguishing it from siblings like get_listing (single listing) and list_categories (categories).

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 this tool (for searching/browsing listings) and provides behavioral hints like 'Newest-first' and 'No personal information is returned; to contact a poster, open the listing URL.' However, it does not explicitly differentiate from siblings (e.g., 'for a specific listing, use get_listing'). The context is clear but lacks explicit exclusions.

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 carries full burden. Explicitly discloses the delayed delivery mechanism (confirmation link, human click required), and instructs the agent to report as pending confirmation rather than sent. 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.

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

Three sentences, each earning its place: purpose, behavioral detail, and action instruction. Front-loaded with primary action. No redundancy or fluff.

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, but description covers what to expect: pending confirmation, user must check inbox. Also instructs on handling reply_to_email. For a 3-param tool, this is 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 covers 100% of parameters, so baseline 3. Description adds context: explains that reply_to_email receives the confirmation link and poster's reply, and instructs not to invent or guess it. Adds meaningful guidance beyond 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?

Clear verb+resource: 'Send a message to the poster of an active SUpost listing.' Unambiguously distinguishes from siblings like create_post (creates a listing) or search_listings (searches listings).

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?

States when to use (to message a poster), but lacks explicit when-not-to-use or alternatives. The behavioral note about delayed delivery is helpful, but no comparison to other tools. Slightly below perfect.

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