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record_compaction_audit

Record context-compaction events to audit token counts and re-injected facts, ensuring transparency across compaction boundaries.

Instructions

Record a context-compaction event with token counts and what was re-injected. Lets developers audit what was remembered across compaction boundaries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idNo
raw_summaryNo
facts_injectedNo
injection_eventNo
pre_compact_tokensNo
post_compact_tokensNo
constraints_injectedNo
Behavior2/5

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

No annotations exist, so the description must disclose behavioral traits. It states it records an event, implying a write operation, but does not mention side effects, whether data is appended or overwritten, permissions, or failure modes. This is a significant gap for a tool with no annotation coverage.

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?

The description is exactly two sentences, front-loaded with the core action and followed by the purpose. Every word adds value with no redundancy or filler.

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

Completeness2/5

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

Given 7 optional parameters, no output schema, and no annotations, the description does not fully equip an agent to use the tool. It lacks information about expected return values, whether any parameters are required in practice, and how this differs from other record_* tools beyond the compaction focus. This is insufficient for the tool's complexity.

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

Parameters2/5

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

Schema coverage is 0%, so the description must compensate. It mentions 'token counts' and 'what was re-injected,' which roughly maps to pre_compact_tokens, post_compact_tokens, facts_injected, and constraints_injected, but it does not explain parameters like injection_event, session_id, or raw_summary. This leaves meaningful ambiguity.

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 uses the specific verb 'Record' with the resource 'context-compaction event' and specifies token counts and re-injected content. It clearly distinguishes from siblings like get_compaction_audit (retrieval) and record_event (generic event) by focusing on compaction-specific auditing.

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 provides clear context: this is for recording compaction events for audit purposes. It does not explicitly mention alternatives or when not to use it, but the specialized language makes the use case evident. There are no exclusions or alternative references, but the context is strong enough.

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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