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gap_list

Read-only

List backlog gaps sorted by most-asked, filterable by topic and status, with paginated results and demand counts.

Instructions

List backlog gaps, most-asked first — the fleet's shared "what we don't know yet" queue. Paginated: returns {items, next_cursor} — pass the returned next_cursor as cursor to fetch the next page. Filter by topic and/or status (open | resolved | promoted); asked_count shows demand for each answer. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
topicNo
app_idYes
cursorNo
statusNo
Behavior5/5

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

Annotations already mark it readOnlyHint=true and destructiveHint=false, and the description confirms 'Read-only.' Beyond that, it proactively discloses pagination behavior (returns {items, next_cursor}), the ordering ('most-asked first'), filter semantics, and the meaning of asked_count. This is exactly the kind of behavioral context that adds value on top of the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

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

The entire description is two sentences, front-loaded with the operation and resource, then efficiently packing pagination, filtering, status values, ordering, and the read-only property with zero filler. Every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the large toolset and 0% schema coverage, the description covers the core behaviors well but is incomplete. The required app_id and the limit parameter are undocumented, and there is no output schema or mention of the item structure beyond asked_count. For a tool that reports 'what we don't know yet,' the agent still needs to guess what each item contains, making it not fully self-sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate, but it does not. It explains cursor usage ('pass the returned next_cursor as cursor') and mentions filtering by topic/status, yet it omits the required app_id entirely and never explains the limit parameter. For a required parameter with zero schema documentation, this leaves a critical gap that the agent cannot infer reliably.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a specific verb-resource pair ('List backlog gaps') plus a sorting qualifier ('most-asked first') and a memorable metaphor ('the fleet's shared what we don't know yet queue'). This clearly distinguishes gap_list from the many other list-style siblings (grove_list_channels, store_list, fork_list) and from the writing tools in its own gap_* family (gap_log, gap_resolve, gap_delete).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear usage context: how to paginate (pass next_cursor back as cursor) and how to filter (by topic and/or status with the allowed status values). It does not explicitly mention when not to use this tool or name an alternative tool, but for a pure listing tool the usage is self-evident from the resource name and the context described.

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

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