supost-mcp

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

No annotations provided, so description fully carries the burden. It discloses that the tool creates only a draft (not published), explains the continue_url workflow, payment requirements, publish parameter limitations (free-tier emails), and security restrictions on sharing the draft link.

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 well-structured and front-loaded with core purpose, but contains several sentences of procedural instructions. While informative, it could be slightly more concise without losing critical guidance.

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 7 parameters, no output schema, and complex workflow (draft vs. publish, payment, continue_url), the description covers all key aspects: creation mechanics, response handling, and security. It sufficiently prepares the agent for correct invocation and user interaction.

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 descriptive field descriptions. The main description adds value beyond schema by explaining how parameters interact (e.g., price required for certain categories, publish effect tied to email tier) and the overall workflow, though it doesn't detail every parameter individually.

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 'Create a DRAFT listing on SUpost on the poster's behalf.' It specifies the verb (create) and resource (draft listing), and distinguishes from sibling tools like get_listing or search_listings by targeting creation of a draft.

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 advises accepting any email without qualification, contrasts draft vs. published behavior, and recommends using publish: true for fast publishing over manual wizard steps. It also warns not to treat payment_required as an error and restricts sharing of continue_url to the poster only.

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 explains the data source (public page), what is included (no personal info), and how to use the returned URL. It also highlights 'stanford_verified' as a trust signal. 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?

The description is concise and front-loaded with the purpose. Every sentence contributes value, though the final instruction to use the URL could be considered slightly redundant but still helpful.

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 a simple one-parameter tool with no output schema or annotations, the description covers the key aspects: what is fetched, how to interpret results, and how to contact the poster. It is sufficiently complete for an agent to use correctly.

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?

With 100% schema coverage and a single parameter (id), the baseline is 3. The description adds value by listing the returned fields (full description, photo URLs, stanford_verified) beyond the schema's 'Numeric listing id'.

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 'Fetch one SUpost listing by numeric id' with a clear verb and resource. It distinguishes from siblings like search_listings (which searches) and create_post (which creates).

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 states when to use the tool (fetching a specific listing by id) and instructs to ALWAYS surface stanford_verified. It does not explicitly describe when not to use or compare to siblings, but the 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 provided, the description carries full burden. It discloses the output format (markdown) and the source URL, and implies read-only behavior. For a simple zero-parameter read operation, this is adequate transparency, though it could mention freshness or authentication 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?

Two sentences, front-loaded with key information. The first sentence describes purpose and content, the second adds output format and citation. No unnecessary 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?

For a tool with no parameters and no output schema, the description fully covers what the tool does, what it returns, and the source. It is complete for its simplicity.

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 exist, so schema coverage is 100% trivially. The description does not need to add parameter info, meeting the baseline of 4 for zero 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?

Description explicitly states it returns verified statistics for SUpost, listing specific metrics (audience size, listing volumes, response rates, response-time medians) and notes the output format. This clearly distinguishes it from sibling tools which handle posts, listings, categories, or messages.

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?

Description implies use when market statistics are needed and includes citation guidance. It does not explicitly state when not to use it or mention alternatives, but the sibling context makes the use case 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. The description implies a read-only, safe operation by returning taxonomy data. For a simple list tool, this is adequate 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?

A single, well-structured sentence that front-loads the main purpose and avoids filler. Every word 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?

Given the simplicity (no parameters, no output schema), the description adequately covers the tool's purpose and output. It is complete for an agent to understand when and why to use it.

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 exist, so schema coverage is 100%. The description adds value by explaining the output's purpose in relation to other tools, going 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?

The description clearly states the tool lists the active category/subcategory taxonomy and explicitly relates it to create_post and search_listings, distinguishing it from 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 tells when to use the tool (to get valid categories for create_post or filters for search_listings). It does not explicitly exclude other uses, but the context is clear for a taxonomy reference tool.

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?

Without annotations, the description carries the full burden. It explains the behavior: returns newest-first public listings, includes opaque cursor for pagination, explains stanford_verified trust signal, and notes no personal info is returned. However, it does not mention rate limits, authentication, 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?

The description is fairly long but front-loaded with key purpose and return fields. It is well-structured with clear sections, though some sentences could be more concise without losing 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?

Given 100% schema coverage and no output schema, the description covers essential aspects: pagination, verification, privacy. It does not detail error responses or every field type, but for a search tool it is sufficiently 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% (baseline 3). The description adds significant value: explains limit defaults, category aliases and IDs, cursor description, max_price inclusivity, and university default. This goes well 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?

The description clearly states the tool searches/browses active listings on SUpost and specifies the returned fields. It distinguishes itself from sibling tools like create_post, get_listing, and list_categories by focusing on searching/browsing public 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 implies usage for searching or browsing listings but does not explicitly state when to use this tool versus alternatives like get_listing (for a single listing) or list_categories. No exclusions or alternative conditions are provided.

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, but the description fully discloses the asynchronous delivery behavior, the need for user confirmation, the fact that replies go to reply_to_email, and warns against inventing the email address. This is exceptional behavioral 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 concise, front-loaded with the main action, followed by crucial caveats in a clear structure. Every sentence adds value without redundancy.

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?

Despite no output schema, the description thoroughly explains the entire message flow, including the pending confirmation state and where replies go. It fully addresses the tool's complexity and provides complete context for an agent.

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 meaningful context: for reply_to_email it warns not to invent or guess, and for post_id it suggests sources like search_listings. This goes beyond the schema's basic 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 'Send a message to the poster of an active SUpost listing,' which is a specific verb and resource, and distinguishes it well 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 explains that the message is not sent immediately and requires a confirmation link click, instructing the agent to inform the user and report the message as pending. This provides clear usage guidance and constraints.

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