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identifier_contract

Identify which key folds merge identifiers and lose data, measuring collision costs and verdicts to distinguish safe from risky normalizations.

Instructions

WHAT ARE THIS STORE'S IDENTIFIERS, and which folds over them would LOSE information?

The question a store outlives its writer to face: someone holds the file months later, the version that wrote it is gone, and whatever deformation happened is already in the bytes. They cannot run a conformance suite. What they need is narrower — which keys are canonical, which folds were DELIBERATE, and which are INVERTIBLE. At remediation time that last distinction is the one that matters: an injective deformation is a backfill job, a fold that maps two keys onto one cannot be undone.

Returns declared (what the running writer promises — byte-exact, case-sensitive, no normalisation) beside measured (what each candidate fold would actually cost on THIS store's keys, independently of the claim). Measured on our own decision store: an 8-character prefix fold would merge 594 groups and lose 1,365 keys, and no field declared any policy at all.

A ZERO COST HAS TWO CAUSES and they render identically, so each fold also carries a verdict. COST_MEASURED means keys demonstrably merge. NOT_YET_MEASURABLE means the population is too small for zero to mean anything — 13 UUID keys against an 8-hex-character fold collide with probability ~1e-8, so a zero there is the absence of a signal rather than a clean bill of health. ZERO_AT_SCALE is the only one that says the fold is harmless on keys like these. Prefix folds also carry threshold_population (how many more keys before a collision is expected, from the per-position perplexity of this store's own keys) and collides_at_length / headroom_chars, which need no model at all: how many characters shorter the fold would have to be before it started merging.

HONEST SCOPE, in limits: declared speaks for the code running now, not for the version that wrote a record last year; and measured sees only surviving keys, so a fold that ALREADY collapsed two of them left no trace of the second. Absence of merging is not proof that none occurred.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Install Server

TDQS

A4/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure and does so thoroughly. It explains that measurements are run on the store's own decision data, that zero cost has two distinct causes resolved by a 'verdict', and that 'measured' can only observe surviving keys so absence of merging is not proof of safety. This is substantive, non-obvious behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long and stylized, opening with a metaphorical narrative before arriving at the actual return values. It is organized into thematic paragraphs and contains valuable detail, but the core function is not front-loaded in a crisp, plain sentence, making it denser than necessary for an agent to parse quickly.

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

Completeness5/5

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

For a complex zero-parameter diagnostic tool with no output schema, the description is unusually complete. It names the return concepts (declared, measured, verdict, limits, threshold_population, collides_at_length, headroom_chars), explains the meaning of each verdict, and states the limits of what the tool can observe. An agent has enough context to understand what the tool reports and how to interpret its results.

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 no required inputs, so the description has no parameter semantics to clarify. Per the zero-parameter baseline, a score of 4 is appropriate; the description does not need to compensate for any schema coverage gap.

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 does state what the tool does: it identifies a store's identifiers and evaluates which candidate folds over them would lose information, returning 'declared' and 'measured' results. It is not a tautology and has concrete detail, but the literary question format and reliance on jargon like 'folds' make it less immediately scannable than a direct verb-and-resource statement, and it does not differentiate itself from sibling tools.

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 provides a clear remediation scenario: when the writing version of a store is gone and a conformance suite cannot be run, the key question is which folds are invertible. However, it never explicitly instructs when to call this tool versus an alternative, and no sibling tools are mentioned, so the usage decision is implied rather than stated.

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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