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popper_hypothesize

Draft and persist split public/private hypotheses for locked contracts, supporting light or ultra reasoning depth and file-based input.

Instructions

Draft (call 1) then persist (call 2 with hypothesis) a split public/private hypothesis for the locked contract.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
depthNoReasoning depth; ultra is a Phase D capability.
hypothesesNoUltraPopper: the K drafted split hypotheses (each with fragments); omit for light mode. Prefer hypothesesDir for large payloads. (A JSON string is accepted and parsed.)
hypothesisNoThe drafted hypothesis to persist; omit on the first call. (A JSON string is accepted and parsed.)
hypothesesDirNoUltraPopper (preferred for large payloads): read every *.json in this dir (each a proposer's hypothesis) instead of passing `hypotheses` inline — avoids giant inline-JSON args. Usually ".popper/inbox".
fragmentAliasesNoUltraPopper: Claude-confirmed canonicalization map { aliasKey: canonicalKey } merging equivalent fragments surfaced in the prior call's mergePlan; omit if none.
hypothesesFilesNoUltraPopper: explicit list of proposer hypothesis JSON files to read + combine (alternative to hypothesesDir).
Behavior3/5

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

No annotations are present, so the description carries the full burden. It reveals the draft-then-persist pattern but lacks detail on side effects, error handling, or implications of the 'locked contract'. Behavioral traits are partially disclosed.

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 a single concise sentence that front-loads the key concept. It could be slightly improved by breaking into two sentences for clarity, but it effectively conveys the essence without waste.

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 tool's complexity (6 parameters, nested objects, no output schema) and the complete schema coverage, the description provides sufficient context for the main workflow. It covers the two-call pattern and parameter usage, though it omits error conditions and return values.

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 description coverage is 100%, and the description adds context beyond the schema, such as preferring `hypothesesDir` for large payloads and omitting `hypothesis` on the first call. This meaningfully supplements the parameter definitions.

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?

Description uses specific verb 'Draft' and 'persist' with resource 'hypothesis for the locked contract'. It clearly distinguishes from siblings like popper_implement or popper_refute by describing a unique two-call process.

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?

Description explains the two-call pattern (call 1 without `hypothesis`, call 2 with `hypothesis`) and provides guidance on parameter usage ('omit for light mode', 'prefer hypothesesDir for large payloads'). However, it does not explicitly state when not to use the tool or list alternatives.

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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