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cellmath

cellmath_compact_session

[SESSION GOVERNANCE] Strict 7-Turn Window Memory Compactor & Tri-State Interceptor (Forget / Store / Retain). Compresses active session into the canonical 4-pack minimal context package [MASTER_SLIM + Organ + Session KV + Node 1] to cap token growth (64.8% savings).

Input Schema

NameRequiredDescriptionDefault
turn_countYesCurrent dialogue turn count in session (triggers 7-turn protocol when >= 7)
target_node_idNoOptional single target pure node ID for next step execution
context_messagesNoOptional session messages or interaction log to compact
interrogation_actionNoTri-state memory decision: "forget" (reset context), "store" (promote to 5-segment cell), "retain" (preserve short-term KV)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description must carry behavioral disclosure. It does convey the compaction behavior and token-cap intent, and the tri-state (forget/store/retain) is named. However, it does not state whether compaction discards raw messages irreversibly, what happens to retained KV on forget, or any permission requirements — meaningful gaps for a state-mutating memory tool.

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?

Only two sentences, but both are dense with bracketed tags, capitalized jargon, and acronyms (MASTER_SLIM, Organ, Node 1) that crowd out the core action. The essential 'compresses the session' idea is present but not cleanly front-loaded.

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?

No output schema and no annotations, so the description should ideally explain the returned package and side effects. It gestures at the '4-pack minimal context package' output but doesn't clarify its structure or what the caller receives on forget versus retain, leaving gaps for a 4-parameter mutation tool.

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 description coverage is 100%, so all four parameters (including the forget/store/retain enum) are already documented in the schema. The description adds the 7-turn threshold context but nothing about target_node_id or context_messages semantics beyond what the schema provides, so baseline 3 applies.

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?

States a specific verb and resource: compresses the active session into a defined 4-pack context package. The bracketed labelling and token-savings metric make the action concrete. It distinguishes itself from siblings like get_session_handover_package by being a compactor rather than a fetcher, though the jargon reduces immediate legibility.

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 'Strict 7-Turn Window' framing implies the trigger condition (echoed by the turn_count schema note '>= 7'), but the description never explicitly states when to call this versus alternatives such as clear_kv_cache_memory or get_session_handover_package. Usage is inferable but not spelled out.

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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