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experience-memory

Save successful action tips as soon as they work and retrieve them for later actions under matching observable conditions; distill reusable procedures into…

Skill by robot-agent-exploration

IndexedApache-2.0★ 184
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Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/robot-agent-exploration-experience-memory

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

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About

Save successful action tips as soon as they work and retrieve them for later actions under matching observable conditions; distill reusable procedures into learned skills with evidence. Use while controlling the robot, when building automation, and at the start of work or after compaction.

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Permissions

What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.

Tools
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Secrets
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Install scripts
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Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/experience-memory

What's inside

Skill name
experience-memory
Description
Save successful action tips as soon as they work and retrieve them for later actions under matching observable conditions; distill reusable procedures into learned skills with evidence. Use while controlling the robot, when building automation, and at the start of work or after compaction.
License
Apache-2.0
Instructions
54 lines in SKILL.md · view on GitHub

Files (2)

  • SKILL.md
  • format.md · references/

SKILL.md (first lines)

# Experience memory

`memory/` belongs to this task and persists across episodes, runs and context
compaction. Keep learned procedures under `memory/skills/`, apart from the provided
skills.

## Retrieve

At the start of work or after compaction, read `memory/INDEX.md` and `memory/TIPS.md`
if present, and open only the learned skills whose conditions match the current scene.
Open linked evidence only when applicability or outcome is uncertain; do not load the
whole history. Current perception and the live tool schemas take precedence over
anything remembered.

## Record tips immediately

- As soon as an action produces a visibly successful, useful result, add or update one
  row in `memory/TIPS.md`. A visible local result is enough; task-level confirmation
  can be added later.
- Record the task phase, the observable preconditions, the tool and arguments or the
  reusable pose relation, the visible effect, and the saved frame paths the tools
  returned. Say what made it work, so later attempts skip the exploration and the
  superseded failures.
- Refine the matching row when the same maneuver improves instead of adding variants.
- Scenes drift between attempts (objects moved back by hand, lighting, layouts): record
  the conditions under which a tip held, not only its numbers.

## Distill

Promote a tip to `memory/skills/<slug>/SKILL.md` plus `evidence.json` when it shows a
reusable motion, contact strategy, recovery or completed procedure. Keep the procedure
short and relative to observed features; keep attempt-specific values and evidence
links in `evidence.json`. Encode poses as the robot's pose-record conventions define
them, when [robot-interface](../robot-interface/SKILL.md) has them.

Update `memory/INDEX.md` with the skill path, tags, confirmation level and the last
episode or date. Mark `task-confirmed` only when the harness's trusted check accepted
an attempt the procedure contributed to, or every `TASK.md` condition was checked in
fresh images; otherwise `observed`. Revise a skill when later evidence contradicts it,
and keep its provenance.

Read [references/format.md](references/format.md) when creating or updating a learned
skill. When a procedure has worked unattended and a persistent library exists, also
contribute it there ([continual-learning](../continual-learning/SKILL.md)).

## Code that runs without memory

A controller run for evaluation may not see the editable workspace: put every
procedure it needs into its code before freezing it. When you continue from carried
notes on a new scene, evidence paths may no longer resolve: rely on the stated
conditions and pose recipes, replay relative recipes from the current measured state,
and reacquire every point a recipe anchors to.

From robot-agent-exploration/rax, Apache-2.0.

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Stars
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Forks
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Last commit (this folder)
Oct 14, 2026 (13 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

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Cite this page

experience-memory skill. Agent Mart. https://agentmart.dev/skills/robot-agent-exploration-experience-memory (last updated 2026-10-24)