What makes Reflexio notable?

957 downloads. Trust evidence available

How should Reflexio be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

Reflexio

Captures user facts and procedural corrections into .reflexio/ so the agent learns across sessions. Use when: (1) user states a preference, fact, config, or...

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

957

Updated

Oct 12, 2026

Version

1.0.10

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 957 downloads reported by the source. Last updated 10/12/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 12, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 12, 2026
Adoption signal: 957 downloadsadoption · observed Oct 12, 2026
Latest release: 1.0.10release · observed Apr 22, 2026
Handshake status: UNKNOWNsecurity

What changed

Newest first. Only changes that point at a source are listed.

Release 1.0.10release
**Reflexio v1.0.10 — Major re-architecture: now runs fully local, storing all memory in .reflexio/ using only OpenClaw primitives.** - Replaced previous server-based design and network-dependent hooks with a native, file-backed skill under the new reflexio-embedded name. - Adds agent-initialization logic: probes and, if approved, auto-configures active-memory and .reflexio/ path registration per agent. - Introduces `reflexio_write_profile`, `reflexio_write_playbook`, and `reflexio_search` tools for profile/playbook management and retrieval. - Documents strict signals and capture requirements (triggers, confirmation/patterns, safety, TTL handling). - Removes network hops, external LLM/service dependencies, and credential prompts: all operation is now fully local and transparent. - Expanded documentation for first-use setup, data safety, and degraded mode operation if configuration steps are declined.
Observed Apr 22, 2026 · source

Install and run

Setup complexity: low.

clawhub skill install s1752wxw7gr3fp8fs91zp3thxn84w528:reflexio

Install using `clawhub skill install s1752wxw7gr3fp8fs91zp3thxn84w528:reflexio` in an isolated environment before connecting it to live workloads.
No published capability contract is available yet, so validate auth and request/response behavior manually.
Review the upstream CLAWHUB listing at https://clawhub.ai/yyiilluu/reflexio before using production credentials.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-yyiilluu-reflexio/snapshot"

Run-check

$0.02 USD

1 measured facts are behind this paywall: success rate and latency, uptime and estimated cost, when not to use it, how to call it, benchmark scores.

Agents pay $0.02 in USDC. A card payment is $0.50, the smallest a card allows.

Documentation

CLAWHUB

153,426 characters of source documentation, loaded on request.

Extracted files

5 files captured from the source.

SKILL.md

---
name: reflexio-embedded
description: "Captures user facts and procedural corrections into .reflexio/ so the agent learns across sessions. Use when: (1) user states a preference, fact, config, or constraint; (2) user corrects the agent and confirms the fix with an explicit 'good'/'perfect' or by moving on without re-correcting for 1-2 turns; (3) at start of a user turn, to retrieve relevant facts and playbooks from past sessions."
metadata:
---

# 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:**

1. Probe current config:
- `openclaw config get plugins.entries.active-memory.config.agents`
- `openclaw config get agents.defaults.memorySearch.extraPaths`
- `openclaw memory status --deep`

2. 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.

3. If `.reflexio/` is not registered as an extraPath:
Ask user: *"I need to register .reflexio/ as a memory path. OK if I run `openclaw config set agents.defaults.memorySearch.extraPaths '[\".reflexio/\"]' --strict-json`?"*
On approval, run the command.

4. 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 set` or `openclaw configure`.

5. On each decline, note the degraded mode but do not block:
- No active-memory → you must run `openclaw memory search` via 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.

6. When all checks resolved (approved or accepted with warning): create the marker:
```bash
mkdir -p .reflexio
touch .reflexio/.setup_complete_<agentId>
```

**If exec is not available** (strict admin policy): fall back to telling the user the exact commands to run manually.

## First-Use Initialisation

Before any write, ensure `.reflexio/` and its subdirectories exist. This is idempotent — safe to run every session:

```bash
mkdir -p .reflexio/profiles .reflexio/playbooks
```

Never overwrite existing files. Never write secrets, tokens, private keys, environment variables, or credentials into `.reflexio/` files. When captu

skills/reflexio-consolidate/SKILL.md

---
name: reflexio-consolidate
description: "Run a full-sweep consolidation over all .reflexio/ files — TTL sweep + n-way cluster merge. Use when the user asks to 'clean up reflexio', 'consolidate memory', 'deduplicate playbooks', or suspects drift across sessions."
---

# Reflexio Consolidate

User-invocable via `/skill reflexio-consolidate`. Same workflow that runs automatically via heartbeat (every 24h of active use), but on-demand.

## What it does

1. TTL sweep: delete expired profile files.
2. For each of profiles and playbooks:
   - Cluster similar files via `memory_search`.
   - For clusters of 2+ members, call `llm-task` with `prompts/full_consolidation.md` to decide consolidate (one-fact-per-file) or keep-all.
   - Apply decisions: write individual fact files, delete originals.

## How to run

Call the `reflexio_run_consolidation` tool. It spawns the consolidator sub-agent and returns a `runId`.

After successful consolidation, call the `reflexio_consolidation_mark_done` tool to update the heartbeat timer.

## When to use

- User asks to "consolidate", "clean up reflexio", "dedupe memory"
- User reports seeing duplicate or contradictory entries in retrieval
- Heartbeat check returns ALERT (automatic trigger)

## When NOT to use

- Routine maintenance — heartbeat handles this automatically.
- Immediately after Flow A/B writes — shallow dedup at write time + Flow C at session end cover the fresh-extraction cases.

skills/reflexio-embedded/SKILL.md

# Reflexio Embedded Skill

## First-time setup per agent

**Steps:**

1. Probe current config:
- `openclaw config get plugins.entries.active-memory.config.agents`
- `openclaw config get agents.defaults.memorySearch.extraPaths`
- `openclaw memory status --deep`

6. When all checks resolved (approved or accepted with warning): create the marker:
```bash
mkdir -p .reflexio
touch .reflexio/.setup_complete_<agentId>
```

**If exec is not available** (strict admin policy): fall back to telling the user the exact commands to run manually.

## First-Use Initialisation

Before any write, ensure `.reflexio/` and its subdirectories exist. This is idempotent — safe to run every session:

```bash
mkdir -p .reflexio/profiles .reflexio/playbooks
```

Never overwrite existing files. Never write secrets, tokens, private keys, environment variables, or credentials into `.reflexio/` files. When captu

prompts/README.md

# Openclaw-Embedded Prompts

LLM prompt templates used by Flow C sub-agents and consolidation.

## Files

- `profile_extraction.md` — extract durable user facts from a transcript
- `playbook_extraction.md` — extract procedural rules from correction+confirmation patterns
- `full_consolidation.md` — consolidate a cluster of similar items into individual facts

## Format

Each file is a `.prompt.md` with YAML frontmatter (matches Reflexio's
`server/prompt/prompt_bank/` convention). Unlike upstream's versioned layout
(`<name>/v<ver>.prompt.md`), we store prompts flat (`<name>.md`) since the
plugin ships atomically with one active version at a time.

```yaml
---
active: true
description: "one-line description"
changelog: "what changed in this version"
variables:
  - var1
  - var2
---

prompt body, with {var1} and {var2} substitution points
```

## Upstream sync

`profile_extraction.md` and `playbook_extraction.md` are ports of Reflexio's
prompt_bank entries. On upstream bumps, review the prompt diff against our
adapted versions. Porting notes will be maintained in
`../references/porting-notes.md` (added in a later phase).

README.md

# Reflexio Embedded

Openclaw plugin for user profile and playbook extraction — learns your preferences, corrections, and workflows across sessions using Openclaw's native memory engine, hooks, and sub-agents. No Reflexio server required.

## Prerequisites

- [Openclaw CLI](https://docs.openclaw.ai) (>= 2026.3.24)
- Node.js

## Install

```bash
# 1. Install and enable the plugin
openclaw plugins install /path/to/this/directory
openclaw plugins enable reflexio-embedded

# 2. Enable the active-memory plugin (required for memory search)
openclaw plugins enable active-memory
openclaw config set plugins.entries.active-memory.config.agents '["*"]'

# 3. Register .reflexio/ as a memory search path
openclaw config set agents.defaults.memorySearch.extraPaths '[".reflexio/"]' --strict-json

# 4. Restart the gateway to pick up changes
openclaw gateway restart
```

Verify it loaded:

```bash
openclaw plugins inspect reflexio-embedded
```

## Uninstall

```bash
# 1. Remove the plugin
openclaw plugins disable reflexio-embedded
openclaw plugins uninstall --force reflexio-embedded

# 2. Clean up state files
rm -f ~/.openclaw/reflexio-consolidation-state.json

# 3. Restart the gateway
openclaw gateway restart
```

Your `.reflexio/` user data (profiles and playbooks) is preserved by default. To remove it:

```bash
rm -rf .reflexio/
```

## What it does

- **Profile extraction** — automatically captures user preferences, facts, and corrections from conversations into `.reflexio/profiles/`
- **Playbook capture** — records recurring workflows and patterns into `.reflexio/playbooks/`
- **Dedup and contradiction resolution** — new entries are compared against existing ones via LLM; overlapping content is merged, contradictions resolved (new wins), and non-contradicted facts preserved
- **Consolidation** — periodic heartbeat-triggered sweep that clusters similar entries and merges duplicates
- **TTL management** — profiles can have time-to-live values; expired entries are swept automatically

## Configuration

Override defaults in your `openclaw.json`:

```json
{
  "plugins": {
    "entries": {
      "reflexio-embedded": {
        "config": {
          "dedup": { "shallow_threshold": 0.4, "top_k": 5 },
          "consolidation": { "threshold_hours": 24 }
        }
      }
    }
  }
}
```

## Learn more

Full project source, design docs, and development setup:
https://github.com/ReflexioAI/reflexio/tree/main/reflexio/integrations/openclaw-embedded

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