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cachly-dev

cachly — AI Cognitive Brain

session_start

Start a session to get a complete briefing: last session summary, recent lessons, focus-area insights, failure warnings, team telepathy, and brain health stats.

Instructions

Single-call session briefing. Call this at the START of every session INSTEAD of multiple separate smart_recall/recall_best_solution calls. Returns: last session summary, recent lessons sorted by recency, relevant lessons for your focus area, open failures (topics with only failure outcomes), brain health stats, team telepathy (what teammates learned this week), predictive pre-warnings (if your focus area has known failure patterns), and memory crystals (compressed wisdom from old sessions). Also saves a session start marker so session_end can compute duration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
instance_idYesUUID of the cache instance
focusNoKeywords for what you plan to work on today (e.g. "deploy infra api"). Used to surface relevant lessons at the top.
authorNoYour name or handle (e.g. "alice"). Enables Team Telepathy — filters YOUR lessons vs TEAM lessons from past 7 days.
providerNoCurrent AI provider (e.g. "claude-code", "copilot", "cursor", "windsurf"). Shown in the briefing header and saved so the next provider can see who was last active.
workspace_pathNoAbsolute path to the project root. If no session_end was found (e.g. context limit hit), reads git log to reconstruct what happened since last session.
Behavior5/5

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

Discloses behavioral trait: saves a session start marker so session_end can compute duration. This is a mutation side effect. Also lists all returned data types comprehensively.

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?

Two sentences: first states purpose and replaces alternatives; second lists returns and side effect. Front-loaded, no fluff.

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

Completeness5/5

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

Given complexity (many return items, no output schema), description exhaustively lists returns and side effect. Complete for agent decision-making.

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

Parameters5/5

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

Schema coverage is 100%, and description adds rich context for each parameter (e.g., focus surfaces lessons, author enables team telepathy, workspace_path reads git log). Adds value beyond schema.

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?

Clearly defines it as a single-call session briefing for start of session, replacing multiple separate calls. Distinguishes from siblings like smart_recall and recall_best_solution by naming them explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explicitly instructs to call at start of every session instead of multiple separate calls. Also notes it saves a marker for session_end, providing clear when-to-use and alternative avoidance.

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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