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Literature Evidence MCP

Literature Evidence MCP

by Furox-Art

export_evidence

Append a JSON evidence record to a local hash-chained JSONL ledger, preserving provenance for literature claims and citations.

Instructions

Append a JSON evidence record to local hash-chained JSONL ledger.

Input Schema

NameRequiredDescriptionDefault
kindYes
payloadYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

C2.7/5.0
Behavior3/5

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

With no annotations, the description must carry behavioral weight. It discloses that the operation appends to a local hash-chained JSONL ledger, which implies durable, tamper-evident, local writes. However, it omits error behavior, idempotency, permission requirements, and whether an existing chain is required.

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?

It is a single front-loaded sentence with no filler. While very short for the tool's complexity, the sentence itself earns its place and is not padded.

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

Completeness2/5

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

The tool has two undocumented required parameters, a nested payload object, no annotations, no output schema, and 0% schema description coverage. A single-sentence description is not enough for an agent to call this tool correctly.

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

Parameters1/5

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

Schema description coverage is 0% for both required parameters. The description never explains what 'kind' should contain or what shape the 'payload' object takes, leaving the agent with no semantic guidance for either argument.

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 ('Append') and resource ('JSON evidence record to local hash-chained JSONL ledger'), which is more specific than a generic 'export'. It does not explicitly differentiate from siblings like verify_evidence_ledger or build_evidence_graph, so it stops short of a 5.

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 when-to-use guidance, no prerequisites, and no mention of alternative tools. The agent is left to infer that this is the write-side counterpart to verify_evidence_ledger.

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