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/asisaga/linkedin.asisaga.com/agent-evolution-agentnpx skills add ASISaga/linkedin.asisaga.com --skill agent-evolution-agentgit clone --depth 1 https://github.com/ASISaga/linkedin.asisaga.comWhat 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 | $0.00030 | $0.00874 |
| Opus 5 | $0.00015 | $0.00437 |
| Sonnet 5 | $0.00006 | $0.00175 |
| Haiku 4.5 | $0.00003 | $0.00087 |
Grade A, and why
agent-evolution-agent 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 2d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Evolution Agent
Role: Meta-Intelligence Self-Evolution Specialist
Scope: .github/ agent ecosystem
Version: 1.2 - High-Density Refactor
Purpose
Meta-agent implementing dogfooding principle: agents improve agents using same standards they enforce. Optimizes context window usage and maximizes spec leverage.
When to Use This Skill
Activate when:
- New specs added to
.github/specs/ - Agent prompts become outdated/verbose
- Duplicate knowledge across agents/specs
- Context window efficiency needs improvement
- Agent quality metrics show issues
Core Principles
Dogfooding: Agents improve agents
- Code agents → clean separation | Agent prompts → zero-duplication
- Domain agents → semantic | Agent structure → semantic
- Docs agents → spec refs | Agent prompts → spec refs
Spec-Driven: Detailed knowledge in specs, not prompts
Continuous: Auto-adapt to codebase changes
Measurable: Track quality metrics
→ Complete architecture: .github/docs/dogfooding-guide.md
Quick Workflows
1. Quality Audit
./.github/skills/agent-evolution-agent/scripts/audit-agent-quality.sh
# Shows: optimal vs needs improvement, spec coverage, context efficiency
2. Spec Sync Check
./.github/skills/agent-evolution-agent/scripts/find-related-agents.sh <spec-file>
# Shows: agents that should reference the spec
3. Duplication Detection
./.github/skills/agent-evolution-agent/scripts/detect-duplication.sh
# Shows: duplicate content across agents
4. Improvement Recommendations
./.github/skills/agent-evolution-agent/scripts/recommend-improvements.sh
# Shows: priority-ranked improvement actions
5. Metrics Tracking
./.github/skills/agent-evolution-agent/scripts/track-metrics.sh [--history]
# Shows: quality trends over time
→ All scripts: scripts/README.md
Target Metrics
Instruction files: ≤200 lines
Prompt files: ≤400 lines
Skill files: ≤150 lines
Spec references: ≥3 per agent
Spec coverage: ≥80% average
What ships with it
9 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.
- references/SELF-LEARNING-ARCHITECTURE.md 9.6 KB
- scripts/audit-agent-quality.sh 4.3 KB runs code
- scripts/detect-duplication.sh 4.0 KB runs code
- scripts/find-related-agents.sh 3.9 KB runs code
- scripts/measure-context-efficiency.sh 5.8 KB runs code
- scripts/README.md 6.4 KB
- scripts/recommend-improvements.sh 5.9 KB runs code
- scripts/sync-agents-with-specs.sh 5.0 KB runs code
- scripts/track-metrics.sh 6.2 KB runs code
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.
- 2d ago First seen · 135 lines · 30 tokens per session scan A 7980cde1ba80
agent-evolution-agent is a skill published in the GitHub repository ASISaga/linkedin.asisaga.com (0 stars, last pushed 4mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 874 once invoked, about $0.0002 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 2026-08-31.
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