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supersession_report

Generate a correction ledger of superseded or reverted facts by key, with counts per policy, current standing value, and full ordered history for each corrected key.

Instructions

The correction ledger: which facts have been superseded/reverted, by key — the auditable 'what changed and what's current' view that an append-only-plus-supersession store can produce and a plain vector store cannot. Counts per policy, and by_key: per corrected key, how many values were retired and by which policy, and current (the standing value: its object, else the first 120 characters of its text; null when the key has none). history(key) gives every value in order.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.20.1

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden and does disclose key behavioral details: counts per policy, per-key retired value counts, the current standing value with a truncation rule for text, null handling, and history ordering. It does not explicitly state read-only behavior or auth requirements, but as a report tool the output-focused transparency is substantial.

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 front-loaded with the core identity ('correction ledger') and packs in useful output semantics without gross bloat. The clause about what a plain vector store cannot produce adds conceptual context but is not strictly necessary, keeping this from a 5.

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?

There is no output schema, but the description explains the main return sections and edge cases in detail. The only gap is that 'history(key)' appears to be a callable function while the input schema is empty, which could confuse an agent about how to invoke it, but the overall tool behavior is adequately covered.

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?

The tool has zero parameters and schema coverage is 100%, so the baseline is 4. The description adds semantic meaning to the output sections (by_key, current, history) rather than parameter details, which is appropriate given the empty input 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 identifies the tool as a correction ledger for superseded/reverted facts, specifically by key, and frames it as the auditable what-changed-and-what's-current view. This is specific enough to distinguish it from the many audit/history sibling tools, and the contrast with a plain vector store reinforces its unique purpose.

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 when to use it (when you need an auditable view of superseded/reverted facts and current values), but it does not explicitly name sibling alternatives or state when not to use it. The phrase 'auditable ... view' gives context without clear exclusions or routing to alternatives like audit_bundle or history.

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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