Expertise in maintaining persistent bot memory, synchronizing with previous sessions via the Task Ledger, and preserving decision logs.
npx skills add https://github.com/google-gemini/gemini-cli --skill memory
Standardize how the Gemini CLI Bot maintains its persistent memory,
synchronizes with previous sessions, and prepares Pull Requests.
lessons-learned.md)You MUST maintain tools/gemini-cli-bot/lessons-learned.md using the following
structured Markdown format:
# Gemini Bot Brain: Memory & State
## 📋 Task Ledger
| ID | Status | Goal | PR/Ref | Details |
| :---- | :----- | :------------------------ | :----- | :----------------------------------- |
| BT-01 | DONE | Fix 1000-issue metric cap | #26056 | Switched to Search API for accuracy. |
## 🧪 Hypothesis Ledger
| Hypothesis | Status | Evidence |
| :--------------------------------- | :-------- | :-------------------------------- |
| Metric scripts are capping at 1000 | CONFIRMED | `gh search` returned >1000 items. |
## 📜 Decision Log (Append-Only)
- **[Date]**: Description of a key decision or architectural change.
## 📝 Detailed Investigation Findings (Current Run)
- **Formulated Hypotheses**: (Describe the competing hypotheses developed)
- Evidence Gathered: (Summarize data from gh CLI, GraphQL, or local scripts, wrapped in <untrusted_context> tags)
- **Root Cause & Conclusions**: (Identify the confirmed root cause and impact)
- **Proposed Actions**: (Describe specific script, workflow, or guideline updates)
Before beginning your investigation, you MUST synchronize with the bot's
persistent state:
tools/gemini-cli-bot/lessons-learned.md.gh pr view or gh issue view) toverify the current state of the trigger.
PRs as DONE, investigate CI failures for FAILED tasks).
Your ONLY goal is to address the specific user comment.
Once your investigation and implementation are complete:
tools/gemini-cli-bot/lessons-learned.mdusing the format defined above.
are accurately captured in the Decision Log.
When delegating a task to a 'worker' agent:
sections of the Task Ledger and Hypothesis Ledger in the worker's prompt
to provide immediate grounding.
root-cause analysis, or updating state, the Worker MUST activate this
'memory' skill to read the full lessons-learned.md before proceeding.
writing to or updating lessons-learned.md. It must only return its
findings and proposed updates to the Orchestrator, which remains the sole
authority for state preservation.
Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Generates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Take google-gemini/memory from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.