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create_finding

Record a claim about the target together with the evidence behind it. The Gateway checks the evidence: an artifact or entity that doesn't exist in this workspace is rejected with an explanation, and a finding can't be confirmed without at…

Instructions

Record a claim about the target together with the evidence behind it. The Gateway checks the evidence: an artifact or entity that doesn't exist in this workspace is rejected with an explanation, and a finding can't be confirmed without at least one piece of evidence - so cite artifacts from list_artifacts, and say where (for example "com/acme/Api.java:12"). It is saved as unverified unless you set a status, and with source "ai". Returns the created finding; change it later with update_finding. Creates the workspace if it doesn't exist.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
claimYesThe claim, one clear statement, e.g. "The login request sends the password over cleartext HTTP". Must not be empty.
statusNoDefaults to "unverified". "confirmed" needs at least one piece of evidence.
evidenceNoEvidence for the claim. Each item cites an artifact from list_artifacts and can add the graph entity it is about, where in the artifact, and a note. Every cited artifact and entity must exist in this workspace, and an entity must have been observed in the artifact it is cited with.
reasoningNoWhy the evidence supports the claim. Optional.
workspaceNoWorkspace name (not id). Created if it doesn't exist, and this call is recorded as a job in its history. Defaults to "default".
confidenceNoHow sure you are. Optional.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.3.19

TDQS

A4.8/5.0
Behavior5/5

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

Annotations cover the safety profile (readOnlyHint=false, destructiveHint=false), and the description adds substantial behavior beyond them: the Gateway validates evidence, rejects non-existent artifacts/entities, defaults status to unverified and source to 'ai', and creates the workspace if missing. That is exactly the operational context an agent needs before calling.

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?

Dense but front-loaded: the core action and evidence-checking rule come first, then defaults, return, and follow-up tool. Every sentence carries information, though the run-on structure could be trimmed slightly.

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?

No output schema exists, yet the description states that the created finding is returned and how to modify it. Combined with the validation and defaulting rules, an agent has everything required to invoke a 6-parameter mutation tool correctly.

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 the schema already documents each field; the description reinforces the evidence semantics with a concrete location example and the artifact/entity existence constraint. It adds meaning beyond the schema rather than merely repeating it, though the gain is modest given full coverage.

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?

States a specific verb and resource: recording a claim plus its supporting evidence as a finding. It is clearly distinguished from siblings list_findings (reading) and update_finding (changing later), so an agent can route correctly without opening any schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly routes the agent to list_artifacts for citation and to update_finding for later changes, and states the condition that a confirmed finding needs evidence. This is when-to-use and when-not-to-use guidance, not just a restatement of purpose.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.