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Skill Lifecycle

skill-ceilf6-frontagent-skill-lifecycle · by ceilf6

Create, evaluate, improve, and benchmark content skills using the local Skill Lab workflow. Use when adding a new skill, tuning an existing skill's trigger behavior, iterating on SKILL.md instructions, or deciding whether a candidate skill should replace the current version.

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Install

$ agentstack add skill-ceilf6-frontagent-skill-lifecycle

✓ scanned · ✓ verified — works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
27d ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming — see below.

Preview Execution monitoring

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About

Skill Creator

Use this skill when the user wants to work on content skills themselves — creating, evaluating, improving, or benchmarking them.

Trigger

  • Requests to create a new content skill
  • Requests to improve or benchmark an existing skill
  • Requests to reduce false positives or false negatives in skill triggering
  • Requests to compare the current skill against a revised candidate

Workflow

  1. Read references/workflow.md to choose the right Skill Lab sequence.
  2. Read references/eval-guidelines.md before creating or editing trigger evals.
  3. If the skill does not exist yet, scaffold a new skill package (e.g. frontagent skill scaffold ).
  4. If the skill does not yet have evals, initialize trigger evals (e.g. frontagent skill init-evals ).
  5. If behavior quality matters, initialize behavior evals (e.g. frontagent skill init-behavior-evals ).
  6. Run a benchmark before making changes (e.g. frontagent skill benchmark ). Use --behavior when behavior evals are available.
  7. When improvement is requested, generate a candidate and compare it with baseline (e.g. frontagent skill improve ). Use --behavior to include behavior scoring.
  8. Only apply a candidate when the benchmark clearly improves and the user wants promotion (e.g. frontagent skill promote or --apply-if-better).

> Platform-specific commands listed above use the frontagent skill CLI. See ADAPTATION.md for how to map these steps to a different platform.

Output Contract

  • Keep the user informed of:
  • where eval files live
  • where candidate skills were written
  • whether benchmark scores improved
  • Prefer benchmark-backed recommendations over intuition.
  • Treat the skill package itself as the artifact under iteration:
  • SKILL.md
  • agents/openai.yaml
  • existing references/ and assets/

Guardrails

  • Do not trust starter evals blindly. Encourage editing them toward real prompts before strong conclusions.
  • Do not auto-apply candidates unless the user requested it or the command explicitly says to do so.
  • Do not silently broaden a skill's scope just to improve trigger rate.
  • Prefer preserving existing references/assets over inventing new file paths.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

  • Author: ceilf6
  • Source: ceilf6/FrontAgent
  • License: MIT
  • Homepage: https://marketplace.visualstudio.com/items?itemName=ceilf6.frontagent

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.