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halvrenofviryel

phionyx-pipeline-mcp

phionyx_response_gate

Validates AI responses against per-action-type thresholds to decide pass, hedge, regenerate, or block, ensuring claims are grounded in evidence and within knowledge boundaries.

Instructions

Response revision gate with action-type-specific thresholds. Call before committing.

Directives: pass | hedge | regenerate | block | require_tool (P1). Different action types trigger different threshold profiles:

  • claim_fixed: strictest (entropy_reject=0.90, phi_min=0.08)

  • deploy: very strict (entropy_reject=0.85, phi_min=0.10)

  • default: standard pipeline thresholds

  • require_tool (P1): for factual action_types (claim_fixed/claim_working/deploy) with no externally-bound evidence, the result carries require_tool{triggered}; with PHIONYX_GATE_REQUIRE_TOOL_ENFORCE=1 an otherwise-passing directive becomes 'require_tool' — bind real evidence (run a tool) before the claim can pass.

  • continuity_binding (P2): the result carries continuity_binding{bound,stale,dds} from the session constraint ledger. compute_dds(confidence, continuity_score) flags "confident while binding unbound/stale"; with PHIONYX_GATE_CONTINUITY_ENFORCE=1 an otherwise-passing directive is downgraded to 'hedge' (re-bind constraints).

  • ask_question / make_claim (Block 15 short-circuit): each identifier in artifact_references is scored against the read-knowledge boundary by phionyx_core's KnowledgeBoundaryDetector; any source not present in artifact_paths_read is assessed outside the boundary → directive='regenerate' with the ungrounded set + the core's reasoning surfaced. Use 'ask_question' BEFORE asking about a named artifact; use 'make_claim' BEFORE asserting what a named source (file, paper, theory, config) says/contains.

Args: action_type: claim_fixed | claim_working | deploy | refactor | investigate | ask_question | make_claim confidence: Your confidence 0.0-1.0 evidence_count: Number of independent test/verification points evidence_type: Type of evidence (see phionyx_verify_claim for options) affects_user_facing: Whether this change is visible to end users artifact_references: Comma-separated artifact identifiers mentioned in the question/claim (file paths, URLs, issue numbers, named sources). Only meaningful when action_type in {'ask_question', 'make_claim'}. artifact_paths_read: Comma-separated artifact identifiers actually opened this turn (Read tool results, gh issue view output, WebFetch URLs). Only meaningful when action_type in {'ask_question', 'make_claim'}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
confidenceYes
action_typeYes
evidence_typeNocode_review
evidence_countYes
affects_user_facingNo
artifact_paths_readNo
artifact_referencesNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

No annotations are provided, so the description carries full burden. It thoroughly discloses thresholds, directive outcomes, and special behaviors like require_tool and continuity_binding, including environment variable effects. This meets the high standard for transparency.

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 well-structured with sections and front-loaded purpose, but it is verbose. Every sentence adds value, but could be slightly more concise without losing critical details. It earns its place given complexity.

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?

Despite having an output schema (not shown), the description covers all behavioral aspects and parameter semantics. Given the tool's complexity with multiple action types and special cases, the description is complete and leaves no critical gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate entirely. It explains all 7 parameters: action_type values, confidence range, evidence_count, evidence_type linking to verify_claim, affects_user_facing boolean, and conditional usage of artifact_references and artifact_paths_read. This adds significant meaning beyond the schema.

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 clearly states it is a 'response revision gate with action-type-specific thresholds' and instructs to 'Call before committing.' The verb 'call' and resource 'response' are specific, and the description distinguishes from sibling tools by detailing unique thresholds and directives.

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?

The description provides explicit when-to-use guidance for each action type, including special cases like 'ask_question' and 'make_claim'. It also instructs to call before committing and explains the conditions for each directive, aiding proper selection.

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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