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Decide Reconciliation Candidate

decide_reconciliation_candidate

Apply, reject, or unreject a duplicate-entity candidate from list_reconciliation_candidates, resolving descendant vs inherited entities in a threat model.

Instructions

Decide a reconciliation candidate from list_reconciliation_candidates. Mutating.

kind is assets, attackers or components; own_qid / inherited_qid are the pair's qualified ids ("child:A1", "parent:A1").

decision="apply" records that the descendant's own entity IS the inherited one: the own entity stays in the model and is left out of its composed view, so the inherited entity is canonical and credit keys on it. The record is dropped when the pair stops matching (an edit, a re-parent). A heuristic-tier candidate is refused unless confirm_heuristic=True acknowledges its structural divergence. The server re-validates the pair (400 when the model has moved since: refresh the list). Bumps the model version; returns {model, controls_carried, controls_orphaned, orphaned_control_ids}.
decision="reject" records "these are NOT duplicates" at org scope, so the pair leaves the active queue for everyone. Idempotent on the pair; no new version. Returns the record; keep its id.
decision="unreject" removes the rejection rejection_id (from list_reconciliation_candidates(disposition="rejected")), returning the pair to the queue. Returns {ok: true}.

503 where composition is not available on the backend.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`kind`	No
`own_qid`	No
`decision`	Yes
`model_id`	Yes
`rejection_id`	No
`inherited_qid`	No
`server_version`	Yes
`confirm_heuristic`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.84.0Oct 4, 2026

TDQS

A4.8/5.0

Behavior5/5

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

No annotations are provided, so the description must carry the full burden, and it does: model version bumps, record dropping on edit/re-parent, idempotency of reject, server re-validation with a 400, and a 503 when composition is unavailable. These are exactly the side effects and failure modes an agent needs before calling a mutating tool.

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?

Front-loaded with purpose and the mutating flag, then organized as per-decision bullets. Dense but every bullet carries operative information; minor redundancy in restating return payloads that the output schema already covers.

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 3-way branching mutating tool with 8 undocumented parameters, the description supplies preconditions, side effects, error codes, and return shapes, more than enough for correct invocation. Nothing an agent needs is missing.

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?

With 0% schema coverage the description must document all 8 params; it explains kind, own_qid/inherited_qid with concrete qualified-id format examples, the decision enum, confirm_heuristic's role, and rejection_id's source. server_version and model_id are used but never explained, leaving a small gap.

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 ('Decide') and resource ('reconciliation candidate'), explicitly ties it to the sibling tool list_reconciliation_candidates, and flags the mutating nature. An agent can immediately tell what this tool does and where its inputs come from.

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?

Breaks out all three decision values with when-to-use semantics (apply = descendant IS inherited, reject = not duplicates at org scope, unreject = restore from rejected queue), names the alternative list call with the disposition filter for unreject, and states the confirm_heuristic precondition for heuristic-tier candidates.

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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