Said It Here

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

No annotations exist, so the description carries the full burden. The verb 'Retrieve' implies a read-only lookup and the enumeration of returned content adds real value, but there is no disclosure of permissions, lookup failure behavior, or what 'verified' means operationally.

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 identifier up front, followed by the content enumeration. Minor adjective padding ('in-depth', 'all verified') slightly inflates it but nothing is wasted.

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, the description must speak to return values, and it does enumerate content types but gives no sense of structure, size, or ordering. For a read tool with one parameter this is adequate but leaves the agent guessing at the response shape.

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 description's 'by slug or URL' merely restates what the schema already documents with an example. Baseline 3 is appropriate since the schema does all the parameter work.

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?

A specific verb ('Retrieve') plus a specific resource ('a specific problem') with an enumeration of what is returned (consensus details, workarounds, quotes, venue distribution). This clearly separates it from the search-oriented sibling, though it never names the sibling 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?

The phrase 'by slug or URL' implies the tool is the detail-fetch step for a known problem, which indirectly distinguishes it from search_problems. However, no explicit when-to-use/when-not guidance or alternative routing is given.

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 present, so the description carries the full behavioral burden. It names data provenance (Reddit, HN, GitHub, Stack Overflow), which is useful, but it does not disclose that this is a read-only search, how results are ranked, whether freshness matters, what source coverage is indexed, or how the limit parameter affects result behavior beyond the schema.

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 definition is a single front-loaded sentence with the action and resource first, followed by useful content/source detail. Some promotional phrasing ('battle-tested community consensus workarounds') is slightly fluffy but does not meaningfully waste space.

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 two-parameter search tool with no output schema and no annotations, the description adequately conveys the search domain and sources. It leaves gaps around return-value shape (dilemma entries, source links), ordering, and search-field coverage, so it is minimally viable rather than 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 description coverage is 100%, so query and limit are already documented with examples and defaults. The description adds no query syntax, search-field scope, or result-ordering semantics beyond what the schema provides, making the baseline 3 correct.

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 (Search) and resource (SaidItHere dilemmas), and enumerates content types and sources, so the agent knows this is a community-problem search tool. Sibling differentiation is only implicit via the verb contrast with get_problem and suggest_dilemma, but the core purpose is unmistakable.

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 by 'Search' and the examples of query topics, suggesting this is the tool for discovery/friction lookups. However, the description never explicitly states when to use it instead of get_problem (single-item retrieval) or suggest_dilemma (submission), nor does it give exclusions or prerequisites.

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; it does disclose that submissions feed an automated crawler pipeline for cross-platform consensus investigation, which explains the downstream effect. It says nothing about authentication, whether the call is synchronous, whether an ID is returned, or rate limits — notable gaps for a write 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?

A single front-loaded sentence with no padding; the verb and resource come first. Slightly heavy on product-specific jargon ('SaidItHere's automated crawler pipeline') that an agent gains little from.

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?

Three flat params and no output schema keep it simple, but for a submission/mutation tool with zero annotations the description omits the key unknowns: what is returned after submission, whether duplicates or failures are handled, and what permissions apply.

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's enumeration of friction/dilemma/gotcha content loosely informs what problem_description should contain but adds no syntax or length guidance 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?

Uses a specific verb (submit) plus a well-scoped resource (new software friction / developer dilemma / tool gotcha) and names the destination pipeline. That clearly separates it from the read-oriented siblings get_problem and search_problems, though the differentiation is only implicit.

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 word 'new' hints that this is for fresh submissions rather than existing problems, which weakly implies when to use it over get_problem/search_problems. There is no explicit statement of when not to use it, whether duplicates are rejected, or what to do instead for retrieval.

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