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tag_search_results

Search files with full-text query and add tags to all matching results in one call.

Instructions

Bulk-tag — run an FTS search and append add_tags to every matching file in one call. Side effect: each match gets addTags applied (additive, idempotent per tag); the matched files themselves are NOT modified beyond their tag links. Per-file failures isolated to errors[]. No external auth or rate limits. There is NO dry-run flag, so ALWAYS run search with the same query first to verify the match set before tagging. The tags[] filter requires existing tags to ALL match (it scopes the search; it does not control which tags get added). Returns {matched_count, tagged_count, tags_applied, tagged_ids, errors}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesFull-text search query
add_tagsYesTags to add to every matching file
project_idNo
tagsNoFilter — only matches that already carry ALL of these tags
favoriteNo
Behavior5/5

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

No annotations provided, so the description carries full burden. It discloses side effects: 'each match gets `addTags` applied (additive, idempotent per tag); the matched files themselves are NOT modified beyond their tag links.' It also mentions per-file failure isolation in `errors[]`, absence of external auth/rate limits, and return fields. This is comprehensive transparency.

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 a single, dense paragraph with no superfluous words. Every sentence provides essential information, making it efficient and easy to parse.

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

Completeness4/5

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

The description covers the tool's core behavior, side effects, failure handling, and return structure (no output schema provided). It mentions all five parameters but lacks detail on `project_id` and `favorite`. Given the tool's complexity and absence of annotations/output schema, it is largely complete.

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

Parameters4/5

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

Schema coverage is 60%. The description adds meaning by clarifying the `tags[]` filter ('requires existing tags to ALL match (it scopes the search; it does not control which tags get added)') and that `add_tags` are tags to add to every match. It does not elaborate on `project_id` or `favorite`, but overall it adds value beyond the schema.

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's purpose: 'Bulk-tag — run an FTS `search` and append `add_tags` to every matching file in one call.' It uses a specific verb ('bulk-tag') and resource (search results), distinguishing it from siblings like `add_tags` (single file) and `search` (just 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 provides explicit guidance: 'There is NO dry-run flag, so ALWAYS run `search` with the same query first to verify the match set before tagging.' It also explains the `tags[]` filter role. However, it does not explicitly contrast with sibling tools or state when not to use it.

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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