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 ivegamsft/basecoat --skill agentic-sdlc-autonomygit clone --depth 1 https://github.com/ivegamsft/basecoatWrote 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/ivegamsft/basecoat/agentic-sdlc-autonomy)<a href="https://agentmods.dev/skills/ivegamsft/basecoat/agentic-sdlc-autonomy"><img src="https://agentmods.dev/badge/skills/ivegamsft/basecoat/agentic-sdlc-autonomy.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00091 | $0.00627 |
| Opus 5 | $0.00046 | $0.00313 |
| Sonnet 5 | $0.00018 | $0.00125 |
| Haiku 4.5 | $0.00009 | $0.00063 |
Grade A, and why
agentic-sdlc-autonomy 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 4d 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.
What it actually says
Agentic SDLC Autonomy Skill
Rules-based autonomy model: agents execute throughput, CI verifies, policy classifies risk, and humans approve irreversible changes.
When to Use
- Auditing repo governance posture against A0-A5 autonomy levels
- Scoring maturity for branch protection, merge queue, deployment lanes, DB/IaC controls, and runner isolation
- Classifying PR risk and routing to auto-merge or human approval
- Detecting policy-versus-settings drift
Autonomy and Risk Model
| Band | Meaning | Typical path |
|---|---|---|
| A0-A1 | Observe and safe edits | docs/tests/lint and non-runtime refactors |
| A2-A3 | Bounded change and auto-merge eligible | app/package changes with required checks |
| A4 | Non-prod execution eligible | preview/staging actions when policy allows |
| A5 | Human-gated only | prod cutover, prod DB migration, IaC apply, secrets/auth/protection changes |
Risk mapping: low (A1-A3), medium (A2-A4), high (A5), and critical (plan-first plus A5).
For risk path/keyword rules see references/autonomy_policy.md.
For PR risk classification script see scripts/classify_pr_risk.py.
For output templates see references/report_templates.md.
Modes and Output
- Audit — evidence-based posture review. Output: summary, drift table, risk register.
- Measure — 0-5 governance scorecard with queue metrics. Output: score and gap list.
- Implement — phased policy/workflow/script changes, report-only first. Output: plan and rollback path.
- Operate — PR risk classification and routing. Output: risk level, autonomy level, decision, and labels.
Related Assets
agents/agentic-sdlc-autonomy.agent.mdskill:ci-auditskill:flow-auditskill:flow-admission-controlskill:human-in-the-loop
What ships with it
4 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.
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.
- 4d ago First seen · 65 lines · 91 tokens per session scan A 1dbebe30c53e
agentic-sdlc-autonomy is a skill published in the GitHub repository ivegamsft/basecoat (4 stars, last pushed today), licensed MIT. It adds 91 tokens to every session and 627 once invoked, about $0.0005 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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