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tugudush
by tugudush

bb_search_code

Search code across a Bitbucket workspace, using filters for repository, language, and file extension to locate specific code snippets.

Instructions

Search for code content within a workspace. Supports filtering by repository, language, and file extension.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number for pagination
filterNoJMESPath expression to filter/transform structured response data. Applied before format conversion. Example: "values[].{name: full_name, lang: language}" — see https://jmespath.org for syntax
pagelenNoNumber of items per page (max 100)
languageNoFilter code search by programming language
extensionNoFilter code search by file extension
repo_slugNoRepository slug to limit search to specific repository
workspaceYesThe workspace to search in
search_queryYesSearch query for code content
output_formatNoResponse format: "text" (default, human-readable), "json" (structured JSON), or "toon" (Token-Oriented Object Notation — compact tabular format that reduces LLM token consumption by 30-60%)
Behavior3/5

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

With no annotations provided, the description carries the full burden. It conveys the core search behavior and filter capabilities but does not disclose pagination behavior, output defaults, or any potential side effects. For a search tool, this is adequate but could be more detailed.

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 long, front-loaded with the core purpose, and contains no filler. Every word earns its place.

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?

For a search tool with 9 parameters, the description captures the essential function and primary filters. Pagination and output_format are documented in the schema, so their absence is not a gap. The lack of an output schema means return values are not explained, but that is not required in the description.

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 coverage is 100%, so the schema fully documents all parameters. The description's mention of filters (repo, language, extension) mirrors existing schema descriptions and adds no new semantic value beyond what the schema already provides.

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 defines a specific action ('search') on a specific resource ('code content within a workspace') and mentions key filtering dimensions (repository, language, file extension), which distinguishes it from sibling tools like bb_search_repositories.

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 context for using this tool is clear: it is for searching code content. However, it does not explicitly mention when not to use it or point to alternatives like bb_search_repositories, which would be helpful but is not strictly necessary.

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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