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VeritasActa

acta-mcp

by VeritasActa

acta_contribute

Submit questions, factual claims with sources or reasoning, opinion/hypothesis with uncertainty, or predictions with resolution criteria and date to the Acta public record.

Instructions

Submit a typed contribution to the Acta public record. Questions have no evidence burden. Factual claims require a source or reasoning. Opinion/hypothesis claims require uncertainty. Predictions require resolution criteria, date, source, and rule.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesFull text of the contribution
typeYesContribution type
topicYesTopic slug (e.g. "ai-regulation-2026")
sourceNoURL to supporting evidence (required for factual claims)
categoryNoRequired for claims
reasoningNoReasoning (alternative to source for factual claims)
provenanceNoOptional AI authorship metadata
uncertaintyNoUncertainty statement (required for opinion/hypothesis claims)
resolution_dateNoISO-8601 future date (required for predictions)
resolution_ruleNoWho/what triggers resolution (required for predictions)
resolution_sourceNoAuthoritative source for resolution (required for predictions)
resolution_criteriaNoHow to determine if confirmed/refuted (required for predictions)
Behavior3/5

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

With no annotations provided, the description bears the full burden. It discloses the submission process and field requirements based on type, but omits behavioral details like authentication needs, reversibility, or rate limits. The description is adequate but not comprehensive.

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 concise and well-structured, starting with a clear purpose statement followed by a bulleted list of rules for each contribution type. Each sentence earns its place, providing essential guidance without unnecessary detail.

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?

Given the tool's complexity (12 parameters, nested objects, no output schema), the description adequately explains the field requirements per type but lacks information about return values, error handling, or success behavior. This leaves some gaps for an agent to understand the full invocation context.

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 100%, but the description adds significant meaning beyond the schema by explaining the conditions under which parameters are required (e.g., source/reasoning for factual claims, uncertainty for opinions/hypotheses, resolution fields for predictions). This adds valuable context for correct parameter selection.

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 tool's purpose: submitting typed contributions to the Acta public record. It distinguishes contribution types (question, claim, prediction) and specifies their requirements, differentiating it from sibling tools like acta_query or acta_respond.

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

Usage Guidelines4/5

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

The description provides explicit guidelines for when to use each contribution type (questions have no evidence burden, factual claims require source or reasoning, etc.). While it doesn't explicitly state when not to use the tool, the context is clear given sibling tools cover different actions.

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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