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templetwo
by templetwo

metabolize

Detect contradictions, stale threads, and aging hypotheses in the chronicle, archive test artifacts, and deduplicate self-model for clean persistent memory.

Instructions

Run a metabolism cycle on the chronicle. action='detect' (default) is eyes-only: reports contradictions, stale threads, aging hypotheses. action='archive_test_artifacts' moves stress-test pollution (STRESS TEST, Unicode test, monomorphic fillers) out of insights/ into chronicle/.archive_test_artifacts/ — reversible. action='dedup_self_model' removes duplicate + test-pollution observations from self_model.json, archiving originals to self_model_archive.jsonl. action='hygiene' runs both archive_test_artifacts and dedup_self_model. Reversible: archives preserve everything, nothing is hard-deleted.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionNoWhat to do. 'detect' = eyes-only digest. Other actions actually move data.detect
max_age_daysNoFor detect: threads older than this are flagged as stale
detect_contradictionsNo
detect_staleNo
Behavior4/5

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

With no annotations provided, the description bears full responsibility. It clearly states that actions move data but are reversible ('archives preserve everything, nothing is hard-deleted'), and describes the effects of each action. It could add detail on auth needs or rate limits, but it is sufficient.

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 concise single paragraph that efficiently lists actions and their effects. It is front-loaded with the main purpose and clearly separates actions. One minor improvement could be bullet points for readability, but it is not wasteful.

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 moderate complexity (4 actions, 4 params, no output schema), the description covers core behaviors and reversibility. It could mention what the detect output looks like or additional constraints, but it is mostly complete for an agent to invoke correctly.

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 50% (only action and max_age_days have descriptions). The description adds meaningful context: it explains the 'detect' action default behavior, that other actions move data, and that max_age_days is for flagging stale threads. For the other two boolean parameters, no extra info is provided, but the defaults imply their roles.

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: 'Run a metabolism cycle on the chronicle' and enumerates specific actions (detect, archive_test_artifacts, dedup_self_model, hygiene). This distinguishes it from sibling tools like 'archive_exchange' or 'dedup' which are more specialized.

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 explains when to use each action (e.g., 'detect' for eyes-only digest, 'hygiene' for both archive and dedup) and notes reversibility. However, it does not explicitly state when not to use this tool or compare it to alternatives, so it lacks exclusions.

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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