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chimera_fracture

Optimize documents and compress conversation messages to fit a token budget, with optional lossy dropping of low-importance content when budget exceeded.

Instructions

Full pipeline: optimize documents → compress messages → budget gate. Returns quality_passed, budget_remaining, lossy_dropped_count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
messagesNoConversation history [{role, content}]. Compressed to fit token_budget before processing.
documentsNoDocument strings to optimise and compress.
token_budgetNoMaximum tokens for the compressed output. Default 1500.
allow_lossyNoWhen True and token_budget is exceeded, drop lowest-importance messages until the budget is met. Default False (lossless).
focusNoOptional task focus/query. Used by quantum compression to retain the most relevant facts.
algorithmNoCompression algorithm. quantum = query-aware salience selection. classic = legacy whitespace/filler compression.quantum
Behavior3/5

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

No annotations provided, so the description must carry behavioral info. It explains the pipeline steps and return values, but does not disclose side effects, auth needs, or whether data is mutated.

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

Conciseness5/5

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

Extremely concise: two sentences that front-load the purpose and return values. Every part is informative.

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

Completeness3/5

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

For a tool with 6 params, no output schema, and no annotations, the description explains the pipeline and return fields but lacks detail on return types or edge cases.

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

Parameters3/5

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

Schema coverage is 100%, so the description does not need to add much parameter meaning. The description adds no extra details beyond what the schema already provides.

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 it is a 'full pipeline' combining optimization, compression, and budgeting, and specifies three return values. This distinguishes it from sibling tools that perform only individual steps.

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 usage when an integrated pipeline is desired, but does not explicitly state when to use this tool vs alternative siblings or provide 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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