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List Decisions

list_decisions

Check a model's decision ledger before raising proposals or asking for judgments, so you don't repeat rejected or already accepted outcomes.

Instructions

List the decision ledger of a model: every judgment recorded on it (finding dismissed or remediated, risk accepted, not-applicable declared, proposal accepted / rejected / reverted, escalation resolved), newest first, with who made it and whether it was within the workspace's delegation policy. Read-only; no side effects.

Call this BEFORE raising a proposal or asking for a judgment, so you do not propose what a person rejected or ask again for what was already decided.

The ledger is append-only. There is no tool that edits it; to undo an accepted proposal, revert or re-decide, never edit the record. Rows with outcome == "refused" are judgments a program was refused; their escalation, if any, is in list_proposals. agent is null for a person's decision.

Input Schema

TableJSON Schema

Name	Required	Description
`limit`	No	Maximum rows to return. 0 (default) uses the server default.
`decision`	No	Optional kind filter, one of ``finding_dismissed``, ``finding_remediated``, ``risk_accepted``, ``not_applicable_declared``, ``proposal_accepted``, ``proposal_rejected``, ``proposal_reverted``, ``escalation_resolved``. Empty (default) returns every kind.
`model_id`	Yes	ID of the threat model.
`agent_only`	No	Only decisions made by a program (``agent`` not null). Default False.
`server_version`	Yes
`outside_policy_only`	No	Only decisions made outside the delegation policy in force at the time (``within_policy`` false). Default False.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.75.0Sep 6, 2026

TDQS

A4.9/5.0

Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden and does so thoroughly: read-only, no side effects, append-only ledger, no editing tool, special meaning of outcome == 'refused', and agent being null for human decisions. This gives an agent a reliable model of the tool's behavior.

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?

Three dense paragraphs front-load the core purpose, then add usage guidance and behavioral caveats. Every sentence carries distinct information, with no filler or tautology.

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-only list tool with an output schema, this description is complete: it covers ordering, filtering semantics, unusual outcome rows, cross-tool routing to list_proposals, and the append-only data model. An agent can call it and interpret results 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 high (83%), so the baseline is 3. The description adds useful meaning for filters by explaining that agent is null for person-made decisions and that decisions carry a within-policy flag, which maps to agent_only and outside_policy_only. However, the undocumented server_version parameter receives no clarifying context, preventing a 5.

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 opens with a specific verb and resource: list the decision ledger of a model, enumerating the exact judgment kinds and stating the sort order plus included attribution/policy fields. It clearly differentiates from sibling proposal and escalation tools by mentioning where escalation data lives.

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?

It gives explicit when-to-use guidance: call this BEFORE raising a proposal or asking for a judgment, so the agent does not repeat rejected or already-decided actions. It also names list_proposals as the source for escalations and states there is no editing tool, steering agents away from mutation attempts.

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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