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Glama

assess_aop_confidence

Read-onlyIdempotent

Build an OECD-style heuristic confidence summary for an adverse outcome pathway using AOP-, key event-, and KER-level evidence text.

Instructions

Build an OECD-style heuristic confidence summary for an AOP from AOP-, KE-, and KER-level evidence text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
aop_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
aopYes
coverageYes
rationaleYes
key_eventsYes
provenanceYes
limitationsYes
overall_callYes
oecd_alignmentYes
ker_assessmentsYes
empirical_supportYes
supplemental_signalsYes
applicability_summaryNo
confidence_dimensionsYes
overall_applicabilityYes
heuristic_overall_callYes
mechanism_role_summaryNo
biological_plausibilityYes
essentiality_of_key_eventsYes
quantitative_understandingYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.10.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare this a read-only, idempotent, non-destructive, closed-world operation, so the safety profile is covered. The description usefully adds that the output is a 'heuristic' (i.e., not authoritative) summary synthesized across three evidence levels, but says nothing about how evidence is gathered, what happens when evidence is missing, or determinism.

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?

A single sentence with no filler, and the artifact being produced is front-loaded before the evidence scope. It is terse to the point of being dense with jargon, but every clause earns its place.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and annotations cover safety. However, for an analysis tool that depends on pre-existing evidence, the description omits what happens with incomplete evidence and how it relates to the sibling validation tool, leaving real gaps.

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?

With a single parameter at 0% schema description coverage, the description must carry the load. It implies that the lone aop_id selects the AOP and that KE/KER-level evidence is collected internally rather than passed in, which is meaningful, but it never states what identifier format is expected or whether the AOP must be a draft.

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 names a specific verb (Build) and a specific artifact (an OECD-style heuristic confidence summary for an AOP), which is clearly distinct from data-retrieval siblings like get_evidence_matrix or get_aop. It does not explicitly contrast itself with the closest sibling, validate_draft_oecd, so an agent must infer the boundary between 'validate' and 'assess confidence'.

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

Usage Guidelines2/5

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

There is no statement of when to use this tool versus alternatives such as validate_draft_oecd or get_evidence_matrix, and no prerequisites or trigger conditions are given. The only implicit cue is that evidence must already exist at AOP/KE/KER level.

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