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jose-compu

Self-Improving Analytics

by José I. O. · GitHub ↗ · v1.1.0 · MIT-0
cross-platform ✓ Security Clean
94
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Install in OpenClaw
/install self-improving-analytics
Description
Captures data quality issues, metric drift, pipeline failures, misleading visualizations, metric definition mismatches, and data freshness problems to enable...
Usage Guidance
This skill appears coherent and does what it says: it scaffolds .learnings/ logs and injects lightweight reminders via optional hooks. Before enabling: (1) review the scripts (scripts/activator.sh, scripts/error-detector.sh, scripts/extract-skill.sh) to confirm you’re comfortable with their behavior; (2) prefer enabling the UserPromptSubmit activator only (not PostToolUse) unless you want automatic error detection from tool output — PostToolUse reads CLAUDE_TOOL_OUTPUT and may run for many commands; (3) enable hooks per-project or add matcher filters so reminders only run for analytics-related sessions; (4) check file permissions and the paths where the hook is copied (~/.openclaw/hooks, ~/.openclaw/workspace) to avoid global changes you didn’t intend; (5) never copy unreviewed SQL or outputs containing credentials/PII into .learnings/ — the SKILL.md explicitly warns about this. If you want extra assurance, run the extract-skill.sh with --dry-run and test the activator locally before enabling hooks globally.
Capability Analysis
Type: OpenClaw Skill Name: self-improving-analytics Version: 1.1.0 The self-improving-analytics skill bundle is designed to help AI agents track and resolve data quality issues, metric drift, and pipeline failures within an analytics workspace. It utilizes shell scripts (activator.sh, error-detector.sh, extract-skill.sh) and OpenClaw hooks (handler.js) to provide automated reminders and scaffold new skills based on captured learnings. The bundle follows security best practices by explicitly instructing the agent not to log credentials or PII, and the scripts include basic path sanitization and input validation to prevent common command injection risks.
Capability Assessment
✓ Purpose & Capability
The name/description match the provided artifacts: markdown templates, reminder scripts, a hook handler, and helpers to scaffold/promote analytics learnings. There are no unrelated required env vars, binaries, or external download/install steps that would be inconsistent with a logging/reminder skill.
ℹ Instruction Scope
SKILL.md and scripts focus on creating/maintaining .learnings/ files and injecting reminders via OpenClaw hooks. The activator and error-detector are intended to be run as hooks and the error detector reads the CLAUDE_TOOL_OUTPUT environment variable to detect errors; SKILL.md also instructs copying hooks into ~/.openclaw/hooks and enabling them. These actions affect the agent workspace and hook configuration (expected for this skill) — review before enabling, and be cautious when enabling PostToolUse hooks since they run on tool output.
✓ Install Mechanism
There is no install spec that downloads or executes remote code. The package is instruction-plus-local-scripts and hook handlers that run locally. All files are present in the skill bundle; nothing pulls from arbitrary URLs or writes unexpected binaries.
ℹ Credentials
The skill declares no required environment variables or credentials. Scripts do read CLAUDE_TOOL_OUTPUT (an agent-provided variable) to detect errors — this is reasonable for a PostToolUse detector but is not listed as a required env var. The README cautions not to log credentials or PII. Examples reference OpenClaw functions (sessions_send/sessions_spawn) which are platform features, not additional secrets.
✓ Persistence & Privilege
always:false and hooks are opt-in. The skill suggests copying hook files into ~/.openclaw/hooks and enabling them, which is expected for a hook; it does not demand forced always-on installation or modification of other skills' configuration beyond registering its own hook.
How to Use
  1. Make sure OpenClaw is installed (local or Docker)
  2. Run the install command in chat: /install self-improving-analytics
  3. After installation, invoke the skill by name or use /self-improving-analytics
  4. Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.1.0
**Version 1.1.0** - Added stackability contract for multi-skill installations. - Added namespaced logging guidance (`.learnings/analytics/`) for coexistence with other skills. - Added required `Skill: analytics` metadata field and cross-skill precedence/ownership rules. - Clarified hook arbitration model (single dispatcher, dedupe, rate limiting).
v1.0.0
Initial release of the self-improving-analytics skill for structured logging and continuous analytics improvement. - Enables standardized logging of data quality issues, metric drift, pipeline failures, schema changes, and misleading visualizations to Markdown files. - Provides initialization instructions for a `.learnings/` directory with pre-defined files: `LEARNINGS.md`, `DATA_ISSUES.md`, and `FEATURE_REQUESTS.md`. - Outlines clear use cases and quick-reference guidance for when and where to log specific analytics incidents. - Supports promotion of important learnings to data dictionaries, pipeline runbooks, dashboard standards, or SLAs for persistent improvement. - Includes OpenClaw-specific setup and generic integration instructions for other agents. - Provides detailed logging format and workflow to ensure actionable, privacy-conscious analytics learnings.
Metadata
Slug self-improving-analytics
Version 1.1.0
License MIT-0
All-time Installs 0
Active Installs 0
Total Versions 2
Frequently Asked Questions

What is Self-Improving Analytics?

Captures data quality issues, metric drift, pipeline failures, misleading visualizations, metric definition mismatches, and data freshness problems to enable... It is an AI Agent Skill for Claude Code / OpenClaw, with 94 downloads so far.

How do I install Self-Improving Analytics?

Run "/install self-improving-analytics" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.

Is Self-Improving Analytics free?

Yes, Self-Improving Analytics is completely free, licensed under MIT-0. You can download, install and use it at no cost.

Which platforms does Self-Improving Analytics support?

Self-Improving Analytics is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).

Who created Self-Improving Analytics?

It is built and maintained by José I. O. (@jose-compu); the current version is v1.1.0.

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