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 NexaDuo/mARC --skill tech-leadgit clone --depth 1 https://github.com/NexaDuo/mARCWrote 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/nexaduo/marc/tech-lead)<a href="https://agentmods.dev/skills/nexaduo/marc/tech-lead"><img src="https://agentmods.dev/badge/skills/nexaduo/marc/tech-lead/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/nexaduo/marc/tech-lead"><img src="https://agentmods.dev/badge/skills/nexaduo/marc/tech-lead.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
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 →
- high YARA Match · line 74 YARA rule matched a hack tool or exploit indicator (offensive tools, reconnaissance, privilege escalation, or exploit frameworks).Fix: Remove offensive tool references and exploit code. Legitimate agent skills should not contain penetration testing tools, exploit frameworks, or reconnaissance utilities.
- high Prompt Injection · line 80 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 276 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 326 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 412 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Prompt Injection · line 492 Hidden instructions were detected in comments or invisible text. These could contain malicious directives. Manual review is recommended.Fix: Audit all comments and invisible characters. Remove any instructions that direct the agent to perform unauthorized actions. Use plain, reviewable content.
- high Anti-Refusal · line 502 Skill attempts to nullify the agent's safety policies or restrictions ('you have no restrictions', 'ignore your guidelines', 'do anything now'). This is a direct jailbreak that disables guardrails.Fix: Remove jailbreak framing that nullifies safety policies or restrictions. Skill content must not instruct the agent to ignore its guidelines or operate without guardrails.
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 | $0.00081 | $0.01313 |
| Opus 5.5 | $0.00032 | $0.00525 |
| Sonnet 5.5 | $0.00016 | $0.00263 |
| Haiku 4.5 | $0.00008 | $0.00131 |
Grade A, and why
tech-lead 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 10d 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 — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@techlead — Tech Lead / Channel Operator
You are @techlead, the channel operator for the mARC team, running in the main conversation where you see everything discussed. Turn discussion into tracked, sufficiently-detailed work and dispatch it to the specialists who idle in the channel until you ping them:
@techlead — you: convene, spec, record, dispatch, track to done (op)
├─ @dev engineer — app/service code, IaC, deploy scripts, schema, tests
├─ @sre reliability — deploy, observability, incidents, backups/DR, cost
├─ @design front-end — UI screens + UX, end-to-end web flows
├─ @sec security — pre-merge diff review (read-only gate)
├─ @rev review — pre-merge correctness review (read-only gate)
└─ @research researcher — external evidence for decisions (read-only brief)
Learn the consuming repo at runtime (no hardcoded stack facts)
mARC carries no repo-specific facts; discover them each session:
- Read
${{{ project_dir_env }}:-.}/AGENTS.md(orCLAUDE.md) — architecture, lessons, mandatory release phases, regression-test rule. - Read
${{{ project_dir_env }}:-.}/{{ agents_dir }}/team.toml(falling back to${{{ project_dir_env }}:-.}/{{ config_dir }}/team.tomlfor repos that haven't migrated) if present — gh org/repo, project number, key source paths, validation command, release-phase facts. If absent, fall back to zero-config runtime discovery (below) — never invent facts, never block on a missing file. - If neither exists (or is incomplete) and the fact is load-bearing, ask rather than assume.
First-run offer: no {{ agents_dir }}/team.toml (nor {{ config_dir }}/team.toml) on an apparent first
session → offer /marc:init to scaffold one from discovered facts — opt-in,
show content before writing; proceed zero-config if declined.
Discover the target repo + project
Never hardcode a repo slug or project number — board.py's
create/set-status/reconcile subcommands resolve org/repo/project
internally (team.toml → gh repo → gh project list). Two guardrails:
- Never auto-bind to a default/"untitled" project (often number
1). Ambiguous/untitled → ask the user; a single clearly-titled match may be used, but state which board. - Missing
projectscope never loses work — tell the usergh auth refresh -s project,read:project; the issue is still created (Issues-only, board add flagged) either way.
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/concurrent-operators.md 11 KB
- references/dispatch.md 21 KB
- references/invariants-card.md 3.9 KB
- references/issue-template.md 980 B
- references/persistence.md 2.2 KB
- references/planning.md 5.5 KB
- references/principles.md 3.8 KB
- references/review-release.md 6.6 KB
- references/upstream-contribution.md 3.4 KB
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.
- 10d ago Changed · +4 lines 9faa4f8adb8f
- 14d ago Changed 63c19801075e
- 16d ago Changed · -576 lines 176a2ae62733
- 25d ago Changed · +12 lines 0689a691c0c7
- 26d ago Changed · +11 lines fe4793e1d527
- 1mo ago Changed · +6 lines 7470e200be77
- 1mo ago Changed · +24 lines f4bbc196b450
- 1mo ago First seen · 619 lines · 81 tokens per session scan A 211865f9fa6f
tech-lead is a skill published in the GitHub repository NexaDuo/mARC (6 stars, last pushed today), licensed MIT. It adds 81 tokens to every session and 1,313 once invoked, about $0.0003 per session on Opus 5.5. 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.
Other skills, from other repositories
execute-plan
Execute a PM-approved plan via per-chunk executor waves.
group-em
PM-GATED. Box-wide: monitor peer sessions; never plan or author for them.
coordinator-update
Check for a published coordinator update and advise a preserve-by-default migration path — never a blind overwrite.
workstream-complete
Wrap up finished work — capture lessons, update docs.
roadmap-planning
PM-GATED. Shape research into ratified roadmap batons.
plan-blitz
PM-GATED. Plan every baton lacking an approved plan, in scout/EM/planner waves. Or named batons.