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 skills add strikersam/autonomous-ai-agency --skill ecc-harness-patternsgit clone --depth 1 https://github.com/strikersam/autonomous-ai-agencyWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/strikersam/autonomous-ai-agency/ecc-harness-patterns)<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/ecc-harness-patterns"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/ecc-harness-patterns/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/strikersam/autonomous-ai-agency/ecc-harness-patterns"><img src="https://agentmods.dev/badge/skills/strikersam/autonomous-ai-agency/ecc-harness-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Agent Snooping · line 96 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
What 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 5.1 | $0.00021 | $0.01003 |
| Opus 5 | $0.00010 | $0.00502 |
| Sonnet 5 | $0.00004 | $0.00201 |
| Haiku 4.5 | $0.00002 | $0.00100 |
Grade A, and why
ecc-harness-patterns 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 7d 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 — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ECC Harness Patterns Skill
Inspired by: ECC — the definitive cross-harness agent orchestration system
Purpose: Integrate multi-harness patterns from ECC into local-llm-server's agent orchestration layer.
What's Unique About ECC
ECC is a production-grade system supporting 7+ agent harnesses (Claude Code, Cursor, Codex, OpenCode, Gemini, Zed, GitHub Copilot) with:
- Harness abstraction layer — normalize API differences
- Hook lifecycle — session start/pause/stop/resume
- Memory persistence — skills learned across sessions
- Cross-harness routing — intelligent model/capability selection
- 182K+ stars — battle-tested in real workflows
Patterns to Adopt
1. Harness Detection & Adaptation
# agents/harness_adapter.py
class HarnessAdapter:
HARNESSES = {
"claude_code": {"context_key": "workspace", "supports": ["streaming"]},
"cursor": {"context_key": "editor", "supports": ["streaming", "streaming_chunks"]},
"codex": {"context_key": "project", "supports": ["completion"]},
}
def normalize_request(self, harness_id: str, request: dict) -> dict:
"""Convert harness-native request to local-llm-server format"""
2. Session Lifecycle Hooks
ECC's /hooks/session-* pattern applied to local-llm-server:
.claude/hooks/
├── session-start/
│ ├── 10-detect-harness.sh # Identify active harness
│ ├── 20-load-harness-prefs.sh # Load harness-specific settings
│ └── 30-emit-telemetry.sh # Send harness telemetry
├── session-pause/
│ └── 10-checkpoint-state.sh
└── session-stop/
└── 10-summarize-session.sh
3. Cross-Harness Model Selection
Extend router/model_router.py to consider harness capabilities:
class CrossHarnessRouter(ModelRouter):
def select_model(self, task: TaskRequest, harness: str) -> str:
"""Route considering harness limits and preferences"""
# Claude Code + reasoning task → deepseek-r1 (powerful)
# Cursor + quick fix → qwen3-coder (fast)
# Codex + completion → fastest available
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.
- 7d ago First seen · 109 lines · 21 tokens per session scan A 2b11b4a39093
ecc-harness-patterns is a skill published in the GitHub repository strikersam/autonomous-ai-agency (8 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 1,003 once invoked, about $0.0001 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 2026-09-03.
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