agentdb-advanced
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/reasoningbank-learning
Use agentic-flow's ReasoningBank to learn from past work - search similar episodes before a task, record reward, success and critique after it, and read trends. Use when the user wants agents to remember what worked, or asks about ReasoningBank, pattern store/search, or
Claude Code
$ npx -y skills add ruvnet/agentic-flow --skill reasoningbank-learning --agent claude-code
Codex
$ npx skills add ruvnet/agentic-flow --skill reasoningbank-learning -a codex -y
Cursor
$ npx skills add ruvnet/agentic-flow --skill reasoningbank-learning -a cursor -y
Gemini CLI
$ npx skills add ruvnet/agentic-flow --skill reasoningbank-learning -a gemini-cli -y
GitHub Copilot
$ npx skills add ruvnet/agentic-flow --skill reasoningbank-learning -a github-copilot -y
OpenCode
$ npx skills add ruvnet/agentic-flow --skill reasoningbank-learning -a opencode -y
Windsurf
$ npx skills add ruvnet/agentic-flow --skill reasoningbank-learning -a windsurf -y
SKILL.md
reasoningbank-learning.SKILL.mdname: reasoningbank-learning
description: Use agentic-flow's ReasoningBank to learn from past work - search similar episodes before a task, record reward, success and critique after it, and read trends. Use when the user wants agents to remember what worked, or asks about ReasoningBank, pattern store/search, or self-learning.
ReasoningBank learning with agentic-flow
ReasoningBank stores one episode per finished task (task text, reward, success, critique) in AgentDB and finds similar episodes by vector search. The loop is **retrieve, act, judge, store**.
Which tools exist depends on the MCP profile
The plugin's `mcp_profile` setting (default `readonly`) decides what the `agentic-flow` server registers:
| Profile | Search and stats | Store an episode | Spawn an agent | |---|---|---|---| | `readonly` | yes | no | no | | `retrieval` | yes | no | no | | `learning` | yes | yes | yes (`agentic_flow_agent`) | | `admin` | yes | yes | yes |
Tools appear as `mcp__plugin_agentic-flow_agentic-flow__<tool>`. Claude Code asks before each call; the plugin pre-approves none.
1. Retrieve
Call `agentdb_pattern_search` with:
- `task`: the new task in one sentence
- `k`: 3 to 5
- `onlySuccesses: true` for approaches to reuse; `onlyFailures: true` for mistakes to avoid
Read the critiques, not just the rewards.
2. Act
Do the task. Keep the retrieved critique in mind.
3. Judge
Score honestly: `reward` 0 to 1 and `success` true or false. A test suite that passes is evidence; "it looks right" is not.
4. Store (learning or admin profile)
Call `agentdb_pattern_store` with `sessionId`, `task`, `reward`, `success`, and a two or three sentence `critique`. Leave out secrets, keys and personal data.
Trends
`agentdb_pattern_stats` (by task) and `agentdb_stats` (database) report what is stored. Quote their numbers; do not extrapolate them.
From a terminal
`npx agentic-flow reasoningbank status`, `list`, `consolidate` and `help` work outside Claude Code too.
Read more
name: reasoningbank-learning description: Use agentic-flow's ReasoningBank to learn from past work - search similar episodes before a task, record reward, success and critique after it, and read trends. Use when the user wants agents to remember what worked, or asks about ReasoningBank, pattern store/search, or self-learning.
ReasoningBank learning with agentic-flow
ReasoningBank stores one episode per finished task (task text, reward, success, critique) in AgentDB and finds similar episodes by vector search. The loop is **retrieve, act, judge, store**.
Which tools exist depends on the MCP profile
The plugin's `mcp_profile` setting (default `readonly`) decides what the `agentic-flow` server registers:
| Profile | Search and stats | Store an episode | Spawn an agent | |---|---|---|---| | `readonly` | yes | no | no | | `retrieval` | yes | no | no | | `learning` | yes | yes | yes (`agentic_flow_agent`) | | `admin` | yes | yes | yes |
Tools appear as `mcp__plugin_agentic-flow_agentic-flow__<tool>`. Claude Code asks before each call; the plugin pre-approves none.
1. Retrieve
Call `agentdb_pattern_search` with:
- `task`: the new task in one sentence
- `k`: 3 to 5
- `onlySuccesses: true` for approaches to reuse; `onlyFailures: true` for mistakes to avoid
Read the critiques, not just the rewards.
2. Act
Do the task. Keep the retrieved critique in mind.
3. Judge
Score honestly: `reward` 0 to 1 and `success` true or false. A test suite that passes is evidence; "it looks right" is not.
4. Store (learning or admin profile)
Call `agentdb_pattern_store` with `sessionId`, `task`, `reward`, `success`, and a two or three sentence `critique`. Leave out secrets, keys and personal data.
Trends
`agentdb_pattern_stats` (by task) and `agentdb_stats` (database) report what is stored. Quote their numbers; do not extrapolate them.
From a terminal
`npx agentic-flow reasoningbank status`, `list`, `consolidate` and `help` work outside Claude Code too.
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Questions about reasoningbank-learning.
- Which coding agents can use reasoningbank-learning?
- reasoningbank-learning installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.