⏳ This skill is pending AI review.
Scores will appear once the review pipeline completes.
observal-ops
Inspects Observal traces, sessions, rankings, feedback, telemetry health, logs, and Agent insight reports. Use when the user wants operational evidence, current activity, telemetry diagnosis, ratings, report generation, regression analysis, or recommendations grounded in Agent usage.
Choose how to use this skill
You do not need every option. Choose the path your AI client supports. The stable page stays the same; versioned files are immutable.
1. Native installer
This listing has no registered native installer command. Use the complete package or source fallback below, depending on what your client supports.
Do not guess an installer command or replace an existing version without reviewing the diff.
2. Complete package recommended
Download the ZIP when available. It includes SKILL.md plus the references, security notes and version metadata.
No complete ProSkills package is published for this listing yet.3. Prompt-only
Copy the prompt above when the agent can read the stable page or when you want to adopt the workflow without installing a skill.
Need only the instruction file?
Download SKILL.md only if your client requires a single file. The complete ZIP is safer for a full installation because it preserves the references and release context.
No path installs or executes anything by itself. Your agent still needs access to the project files. Before updating, compare the installed version and review the diff.
// RATINGS
Not yet listed on ClawHub or SkillsMP
// README
Agentic Resource Registry
A self-hosted, Apache 2.0 registry for sharing coding agent resources. Formerly Observal.
Set up once, and let your coding agent use Agentic Resource Registry through observal-cli.
If you find Agentic Resource Registry useful, please consider giving it a star. It helps others discover the project and keeps development going.
Formerly Observal. Same code, same maintainers, same Apache 2.0 license. The CLI is still
observal, and oldObserval/Observallinks redirect here.
What is Agentic Resource Registry and what does it solve?
Agentic Resource Registry is a self-hosted, Apache 2.0 registry for sharing coding agent resources across your organization. Every tech-forward organization today creates internal Skills, Agents files, MCP clients. Though the creation of these coding agent resources has been prolific, peer adoption and usage is sparse. Coding agent users today end up creating their own version of such resouces without reusing existing packages.
The cause is largely due to two problems:
-
Lack of a discoverability layer
Organizations store their coding agent resources in siloed git repositories with little to no documentation. Users are not able to locate existing coding agent resources and this results in multiple developers creating the same/similar resources again.
-
Missing feedback loop
Any software where usage patterns are not understood and the principle of user-centric development is violated tends to fade out. Such is the problem with development of MCP clients, Skills and Agent files. Authors publish and maintain these resources with little visibility into how they're actually used. Additionally, Coding agent failures don't trigger static error codes: they hallucinate or provide subtly incorrect answers. This leaves users clueless about what went wrong compounding the feedback problem.
Agentic Resource Registry solves this by providing a centralized discovery layer for coding agent resources alongside useful insights into usage patterns. It turns silent failures into actionable feedback, ensuring internal resources are continuously optimized for the people using them.
Agentic Resource Registry supports Claude Code, Cursor, Kiro, Pi, Copilot, Codex, OpenCode, and other tools.
Why teams use Agentic Resource Registry
- Centralize resources into one platform: Store Skills, MCP clients, hooks, prompts, agent files and sandboxes in one registry.
- Run a governed registry: Review submissions, approve internal agents, inspect version diffs, and give developers one trusted place to install from.
- Render across multiple Coding IDE/CLI: Generate the correct config for each supported harness instead of maintaining separate setup instructions for every harness.
- Let agents use each other: Every approved resource is discoverable over the open ARD standard, and a running agent can hand part of its task to another approved agent, whether it lives in the registry or is a remote A2A service.
- Learn what works: Use real adoption and session data to find which agents, tools, prompts, and workflows are helping teams.
- Replay sessions when needed: Use traces as evidence for debugging, review, audits, and deeper analysis.
Supported harnesses
[ | | Agent health, friction, costs, versions, regressions, or suggestions | [Insight reports](references/insight-reports.md) | | MCP, skill and hook component presence, observed calls, skill loads or hook runs, and attribution coverage | [Insight reports](references/insight-reports.md) | Read the selected reference completely before executing. ## Analysis rules - A zero exit status from telemetry diagnosis can still contain issues or warnings. Read the JSON health fields. - No events is not automatically a hook problem. Check authentication, server reachability, local outbox, and hook state in that order. - Quote report evidence accurately and say when session count is thin. For component reports use `--component mcp|skill|hook NAMESPACE/SLUG` with `insights list|show|generate`; coverage gaps are unknown, never proof of non-use. A skill load or invocation shows its instructions entered context, never that the skill helped; a recorded hook run is a lower bound and never shows what the hook changed. - Only `component_ref` proves an insight suggestion maps to a Registry component. Never reconstruct a component identity from prose. - Lead with reuse suggestions before create-new suggestions. - For logs and traces, summarize the minimum sensitive content needed to answer the question. ## Completion Report the time range, filters, counts, health state, strongest evidence, uncertainty, and concrete next action. Do not present popularity fallback or sparse reports as personalized certainty.README.mdupstream ↗
Contents are not inlined in the catalog. Open the upstream file.
Plain-text copy, no login: /skill-bundles/observal-observal-observal-cli-skills-observal-ops.md