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get-the-code-score

Returns The Code Score (security/code-quality/dependencies, 1000 points) for a project (aggregated) or a single vault. Provide exactly one of project_id or vault_id. Requires full data access (a paid plan; verification-only plans are not included). If the plan doesn't include Code Score access, or it hasn't been generated yet, returns the same response shape with empty sections/priorities rather than an error. Requires X-API-Key (existing users can generate an API key in the web app). If headers aren't supported, pass api_key in arguments.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoOptional API key for clients that cannot set X-API-Key headers.
vault_idNoVault id (from create-code-vault or list_vaults). Returns data for this vault only.
project_idNoProject id (from create_project). Returns data aggregated across all vaults in the project.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden and does so well: it discloses the paid-plan/access requirement, the auth mechanism (X-API-Key) with an api_key argument fallback, and the notable non-error behavior of returning empty sections/priorities when access is missing or data is not generated. These are exactly the traits the agent cannot infer from structured fields.

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 paragraph is front-loaded with the core purpose, then layers constraints, auth, and edge-case behavior in descending priority. Every sentence carries actionable information with no filler.

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?

For a read tool with no output schema, the description covers purpose, parameter exclusivity, access prerequisites, auth, and the empty-response fallback. An agent has everything needed to call it correctly and interpret a non-error empty result.

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 schema already documents vault_id, project_id, and api_key semantics. The description's 'exactly one of' rule and api_key fallback note restate what the schema and its oneOf constraint already express, adding little beyond the structured data. Baseline 3 is appropriate.

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 states a specific verb and resource ('Returns The Code Score') and precisely scopes it to two modes: aggregated across a project or a single vault. This distinguishes it from siblings like get-code-vault-summary, get-code-vault-results, and get_project without the agent needing to open those schemas.

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?

It gives a clear selection rule ('Provide exactly one of project_id or vault_id') that tells the agent how to choose between the two aggregation modes. It does not, however, explain when to prefer this tool over related siblings such as get-code-smells or get-security-issues for the same data.

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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