GnosisLab

Overview Schema Source Related Servers Discussions Admin

record_promotion_decision

Record an attributed, insert-only verdict (promote, reject, hold, rollback) on a candidate, citing evidence and rationale for auditable promotion decisions.

Instructions

Record an attributed verdict on a candidate (RSI Phase 0).

verdict: promote | reject | hold | rollback. Decisions are insert-only — reversal is a new decision ('rollback'), never a mutation. evidence_refs may be sent as a JSON-encoded string list. decided_by is required: attribution is first-class.

Enforcement: verdict enum, non-empty rationale/decided_by, candidate (and contract, if given) must exist.

Input Schema

TableJSON Schema

Name	Required	Description
`bf_2ln`	No	The measured 2 ln BF bound forwarded with computed_rung. Stored for audit.
`verdict`	Yes	promote \| reject \| hold \| rollback — insert-only; reversal is a new 'rollback' decision.
`rationale`	Yes	Non-empty justification — accountability is first-class.
`decided_by`	Yes	Attributable decider (e.g. 'human:<name>' or a protocol/improver id).
`contract_id`	No	Optional contract the decision was scored under; must exist if given.
`candidate_id`	Yes	Candidate the verdict applies to; must exist.
`claimed_rung`	No	Evidence rung this verdict claims (not_worth\|positive\|strong\|very_strong — the Kass–Raftery ladder). Required on 'promote' when the cited contract declares min_evidence_rung.
`computed_rung`	No	Evidence rung the promotion channel measured (forwarded by zetesis record_promotion_verdict — the rung close computed from the arm data). Stored beside claimed for audit; upstream cannot recompute it.
`evidence_refs`	Yes	Evidence_ref IDs (from pull_evidence) the decision cites — ≥1 required; may be a JSON-encoded list.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`status`	No
`decision_id`	No
`claimed_rung`	No
`computed_rung`	No
`declared_rung`	No
`unverified_refs`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.28Oct 5, 2026

TDQS

A3.7/5.0

Behavior4/5

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

With no annotations, the description carries the full behavioral burden and discloses key traits: insert-only semantics, reversal via a new decision, JSON-encoded evidence_refs, required decided_by, and enforcement checks (verdict enum, non-empty rationale/decided_by, existence of candidate/contract). It does not cover permissions or rate limits, but the core mutation and validation behavior is well communicated.

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 the purpose and then uses short paragraphs to cover verdicts, insert-only semantics, and enforcement. It avoids fluff and every sentence contributes relevant constraints or behavior. Minor fragmentation exists, but overall it is efficient and easy to scan.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a 9-parameter mutation tool with no annotations and an output schema, the description provides a complete enough picture: what the tool does, the allowed verdicts, insert-only behavior, required attribution, and validation rules. It does not explain permissions or return values, but the output schema covers returns and no annotations exist to contradict. The remaining gap is minor.

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 all nine parameters in detail. The description repeats the verdict options, evidence_refs JSON-string format, and decided_by requirement, adding little semantic meaning beyond the structured schema. Baseline 3 is appropriate when the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: 'Record an attributed verdict on a candidate (RSI Phase 0).' It clearly distinguishes the act of recording a verdict from list/read siblings like list_promotion_decisions, though it does not explicitly name any alternative tool. The scope is clear enough for an agent to understand the tool's core function.

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

Usage Guidelines3/5

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

It provides an important usage rule: decisions are insert-only and reversal is a new 'rollback' decision, never a mutation. This tells the agent how to handle reversals, but it does not state when to use this tool versus alternatives or what preconditions are needed beyond enforcement rules. Usage context is implied rather than explicit.

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

Deploy Server