Skip to main content
Glama

credence_verify

Mark a constraint as verified by submitting its confirmed value and evidence, recording an audit trail and excluding it from further enforcement.

Instructions

Mark a registered constraint as verified with its confirmed value.

After verification the constraint is excluded from Truth Buffer injection and Consistency Enforcer enforcement. An audit trail is recorded — who verified, on what basis, and what the confirmed value is.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoWho verified this. Use "user" for human confirmation, "api_response" for automated checks, "agent:<name>" for downstream agents, "external_doc" for documentation.user
evidenceNoWhat was checked to confirm this. Strongly recommended. Examples: "checked Stripe dashboard 2026-05-02", "confirmed in production logs", "vendor email attached". An empty evidence string is accepted but leaves no audit basis.
session_idYesSession identifier.
constraint_idYesID from credence_register.
verified_valueYesThe confirmed value (e.g. "100 req/min per Stripe docs §4.2").

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

Despite no annotations, the description discloses important behavioral traits: the constraint is excluded from Truth Buffer injection and Consistency Enforcer enforcement, and an audit trail is recorded. It does not mention permissions or reversibility, but these are less critical for a verification action.

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?

The description is extremely concise: two sentences covering purpose, consequences, and audit. Every sentence adds value with no fluff. Structure is front-loaded with the primary action.

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?

Given the existence of an output schema and the specific nature of the tool, the description covers the main purpose and side effects adequately. It could mention what happens if the constraint doesn't exist or if there are errors, but overall it's sufficient.

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 coverage is 100% with adequate descriptions for each parameter. The tool description does not add additional meaning beyond the schema, so it meets the baseline of 3. No improvements needed.

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 the action ('Mark a registered constraint as verified') and the resource ('constraint'). It also specifies the confirmed value. The tool's role is unique among siblings (e.g., 'credence_register' creates constraints, 'credence_autoverify' presumably automates verification).

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?

The description implies the tool is used after registering a constraint and when manual verification is needed, but it does not explicitly say when to use it versus alternatives like 'credence_autoverify' or when not to use it. No exclusions or prerequisites are given.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Lakshmi-Chakradhar-Vijayarao/credence-ai'

If you have feedback or need assistance with the MCP directory API, please join our Discord server