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find_repos_using_endpoint

Find all repositories in a GitHub organization whose Harden-Runner baseline contains a specified network endpoint (domain or IP substring match). Ideal for auditing which repos contact a given domain for migration planning or security reviews.

Instructions

Find every repo in an org whose Harden-Runner baseline contains a given network endpoint (domain or IP, substring match). Useful for questions like 'which repos contact bun.sh?', 'who still uses registry.npmjs.org?', or migration planning. Fans out one request per repo with bounded concurrency — expect 10–60 seconds on orgs with many repos. Returns only repos that matched — each one has a baseline_url which you MUST surface as a clickable link per repo (not just the first one). NOTE: this tool is single-org. For a tenant-wide sweep, first call list_tenant_github_orgs and then call this per org.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
ownerYesGitHub organization
endpointYesEndpoint substring to search for, e.g. 'bun.sh:443', 'registry.npmjs.org', '8.8.8.8'
concurrencyNoMax parallel requests (default: 10)
Behavior5/5

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

No annotations are provided, so the description fully discloses fan-out with bounded concurrency, expected delay (10–60 seconds), return behavior (only matched repos), and the requirement to surface baseline_url as clickable links per repo. It also clarifies the single-org limitation.

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

Conciseness4/5

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

The description is front-loaded with purpose, then use cases, then technical details. It is efficient with multiple sentences, each earning its place, though it could be slightly more concise without losing meaning.

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?

Despite no output schema, the description explicitly describes the return format (list of repos with baseline_url) and provides instructions for surfacing results. It also covers concurrency, time expectations, and multi-org workflow, making it fully complete for the tool's complexity.

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 100%, so baseline is 3. The description adds value by emphasizing substring matching for endpoint, stating the default concurrency of 10, and bounding concurrency with a max of 50. This goes slightly beyond what the schema 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 states it finds repos in an org whose Harden-Runner baseline contains a given network endpoint via substring match. It uses a specific verb ('Find') and resource ('repos'), and the context (single-org, substring match) distinguishes it from siblings like check_ioc_in_baseline or check_npm_package_exposure.

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 use-case examples ('which repos contact bun.sh?') and addresses multi-org scenarios by referencing list_tenant_github_orgs. However, it does not directly compare with sibling tools or state when not to use.

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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