Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/reflexioai/reflexio/pluginnpx skills add ReflexioAI/reflexio --skill plugingit clone --depth 1 https://github.com/ReflexioAI/reflexioWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00102 | $0.02269 |
| Opus 5 | $0.00051 | $0.01135 |
| Sonnet 5 | $0.00020 | $0.00454 |
| Haiku 4.5 | $0.00010 | $0.00227 |
Grade A, and why
reflexio-embedded scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- reflexio-embedded — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 195 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Reflexio Embedded Skill
Captures user facts (profiles) and procedural corrections (playbooks) into .reflexio/, so the agent learns across sessions. All memory lives in Openclaw's native primitives — no external service required.
First-time setup per agent
If .reflexio/.setup_complete_<agentId> does NOT exist (where <agentId> is your current agent id), perform this one-time check. The setup step runs probing commands via exec and asks for approval before making changes.
Steps:
-
Probe current config:
openclaw config get plugins.entries.active-memory.config.agentsopenclaw config get agents.defaults.memorySearch.extraPathsopenclaw memory status --deep
-
If active-memory is not targeting this agent: Ask user: "To auto-inject relevant facts into each turn, I can enable active-memory for this agent. OK if I run
openclaw config set plugins.entries.active-memory.config.agents '[\"<agentId>\"]' --strict-json?" On approval, run the command. -
If
.reflexio/is not registered as an extraPath: Ask user: "I need to register .reflexio/ as a memory path. OK if I runopenclaw config set agents.defaults.memorySearch.extraPaths '[\".reflexio/\"]' --strict-json?" On approval, run the command. -
If no embedding provider is configured (FTS-only mode): Tell user: "Vector search requires an embedding API key (OpenAI, Gemini, Voyage, or Mistral). The plugin works without one but retrieval quality drops. Would you like guidance on adding one?" If yes, guide them through
openclaw config setoropenclaw configure. -
On each decline, note the degraded mode but do not block:
- No active-memory → you must run
openclaw memory searchvia exec at turn start (see "Retrieval" section below). - No extraPath → WARN the user the plugin cannot function without this step.
- No embedding → continue with FTS-only.
- No active-memory → you must run
-
When all checks resolved (approved or accepted with warning): create the marker:
mkdir -p .reflexio touch .reflexio/.setup_complete_<agentId>
What ships with it
22 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- _meta.json 116 B
- agents/reflexio-extractor.md 2.0 KB
- HEARTBEAT.md 155 B
- hook/handler.ts 6.7 KB runs code
- hook/setup.ts 2.0 KB runs code
- index.ts 13 KB runs code
- lib/consolidate.ts 8.2 KB runs code
- lib/dedup.ts 3.5 KB runs code
- lib/io.ts 4.0 KB runs code
- lib/openclaw-cli.ts 1.8 KB runs code
- lib/search.ts 1017 B runs code
- lib/write-playbook.ts 2.7 KB runs code
- lib/write-profile.ts 2.8 KB runs code
- openclaw.plugin.json 1.5 KB
- package.json 444 B
- prompts/full_consolidation.md 1.9 KB
- prompts/playbook_extraction.md 14 KB
- prompts/profile_extraction.md 8.4 KB
- prompts/README.md 1.1 KB
- README.md 2.4 KB
- skills/reflexio-consolidate/SKILL.md 1.4 KB
- skills/reflexio-embedded/SKILL.md 9.3 KB
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 195 lines · 102 tokens per session scan A 43a83d79a3f9
reflexio-embedded is a skill published in the GitHub repository ReflexioAI/reflexio (338 stars, last pushed 2d ago), licensed Apache-2.0. It adds 102 tokens to every session and 2,269 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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