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cachly-dev

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session_end

Record a session summary of accomplishments and lessons learned to provide context for future sessions. Optionally, analyze git commits to automatically learn from changes.

Instructions

Save a session summary when you finish working. Records what was accomplished, files changed, and lesson count. The next session_start will show this summary as "Last session". Call this when ending a work session, before going idle, or before summarizing. Ambient Learning: if workspace_path is provided, reads git log since session start and auto-learns from commits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instance_idYesUUID of the cache instance
summaryYesBrief summary of what was accomplished this session (2-3 sentences)
files_changedNoKey files changed this session (optional)
lessons_learnedNoNumber of new lessons stored this session (optional)
workspace_pathNoAbsolute path to the project root (e.g. "/Users/you/myproject"). Enables Ambient Learning — reads git log since session start and auto-learns from commit messages.
Behavior3/5

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

With no annotations, the description carries the transparency burden. It explains the summary storage, next session display, and Ambient Learning from git log. However, it does not disclose potential side effects (e.g., whether data is overwritten), response behavior, or error conditions. More detail on the learning process would improve transparency.

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 three sentences long, each serving a distinct purpose: purpose, integration with next session, and additional feature. It is front-loaded with the core action and remains concise without unnecessary details.

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 relative simplicity and the presence of 5 parameters with 2 required, the description covers the essential behavior and the optional Ambient Learning. It could mention return values or error handling, but for a save operation it is reasonably complete.

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 coverage is 100%, but the description adds useful context: it explains that workspace_path enables Ambient Learning and that summary should be '2-3 sentences'. This goes beyond the schema's basic descriptions, providing actionable guidance.

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: saving a session summary when finishing work. It specifies what is recorded (accomplishments, files changed, lesson count) and mentions how it integrates with session_start. This distinguishes it from siblings like session_start and session_ping.

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 explicitly says 'Call this when ending a work session, before going idle, or before summarizing,' providing clear usage contexts. It does not mention when not to use or compare to alternatives like session_handoff, but the guidance is sufficient.

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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