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Search wiki pages

wiki_search_pages

Search wiki pages by literal words in title, description, or path. Returns matching results with total hit count so you know when results are truncated.

Instructions

Full-text search across ok-wiki pages — the first tool to reach for when asked about anything in the wiki. Matching is substring-ish, not semantic: the default search engine is a database LIKE scan over title, description, and path, so search for literal words that would appear on the page rather than paraphrases. Returns { results, totalHits, suggestions }; results are capped at limit, while totalHits reports the true match count so you can tell when you are seeing a slice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathNoRestrict results to pages whose path starts with this prefix, e.g. "projects/". Applied server-side by the search engine.
limitNoMaximum results to return (1-50, default 10). Applied client-side; `totalHits` still reports the true match count.
queryYesSearch terms. Matched substring-ish (database LIKE scan), not semantically — use literal words likely to appear in the page title, description, or path.
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the non-semantic substring matching, the fields searched, the return shape, and the relationship between limit and totalHits. This is substantial and well beyond a minimal disclosure, though it omits potential error cases or rate limits, which are less critical for a search tool.

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 description is two sentences, front-loaded with purpose, and every clause adds value. It explains behavior, return format, and usage without redundancy, making it highly efficient for an agent to parse.

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

Completeness5/5

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

Given no output schema, the description compensates by specifying the return object fields and the significance of totalHits. It also covers matching behavior, field scope, and usage context, making it complete for a search tool with three parameters. No critical gaps remain.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description reinforces the query semantics (literal words, substring matching) but does not add new parameter meaning beyond what the schema already provides. The limit/totalHits relationship is already documented in the schema, so the description adds marginal value.

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 clearly states the tool performs full-text search across wiki pages, with a specific verb ('search') and resource ('ok-wiki pages'). It differentiates from siblings by positioning itself as 'the first tool to reach for when asked about anything in the wiki' and clarifies it matches title, description, and path, distinguishing it from tag-specific search.

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 context on when to use the tool ('first tool to reach for') and how to use it effectively (use literal words, not paraphrases). It does not explicitly name alternatives or exclusion cases, but the behavioral guidance is strong enough for an agent to select it appropriately.

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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