Skip to main content
Glama
cachly-dev

Cachly — AI Cognitive Brain

session_start

Start each session with a single call that delivers summary, recent lessons, focus-relevant insights, failures, brain stats, team telepathy, failure predictions, and memory crystals. Avoids multiple separate lookups.

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.
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses the full list of return fields and the side effect of saving a session start marker. However, it lacks details on idempotency, error handling, or permissions.

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

Conciseness4/5

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

Description is a single paragraph but comprehensive and front-loaded. No wasted words, but could be slightly more structured for readability.

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?

Despite no output schema, the description enumerates all returned items (last session summary, recent lessons, etc.) and explains the side effect. It is complete for a session start tool.

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%, so schema already describes each parameter well. The description adds value for some parameters (e.g., focus, author, workspace_path) by explaining how they influence results, but doesn't add much beyond what schema says.

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 'Single-call session briefing' to be called at the START of every session, replacing multiple separate calls like smart_recall/recall_best_solution. This distinguishes it from its siblings.

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 says when to use (at session start) and when not to (instead of separate calls). Mentions that it saves a marker for session_end, providing a clear usage pattern.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/cachly-dev/cachly-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server