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 harness/harness-ai --skill enforce-slsagit clone --depth 1 https://github.com/harness/harness-aiWrote 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/harness/harness-ai/enforce-slsa)<a href="https://agentmods.dev/skills/harness/harness-ai/enforce-slsa"><img src="https://agentmods.dev/badge/skills/harness/harness-ai/enforce-slsa/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/harness/harness-ai/enforce-slsa"><img src="https://agentmods.dev/badge/skills/harness/harness-ai/enforce-slsa.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00173 | $0.03098 |
| Opus 5 | $0.00086 | $0.01549 |
| Sonnet 5 | $0.00035 | $0.00620 |
| Haiku 4.5 | $0.00017 | $0.00310 |
Grade A, and why
enforce-slsa 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 9d 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.
This is a copy
100% identical to enforce-slsa — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Enforce SLSA
Add an SLSA Verification (SlsaVerification) step to an existing Harness pipeline. The step
verifies SLSA provenance attestations (when enabled) and optionally evaluates OPA policy sets against
provenance data.
This skill only works with existing pipelines — do not create standalone verification-only pipelines.
Prerequisites: SLSA provenance must already exist for the artifact (typically from a provenance
step via /generate-slsa — UI label SLSA Generation). Optional policy sets for provenance
enforcement (/create-policy, harness_list policy_set).
Supported stages: CI, CD (Deployment), and Security. CD requires a containerized step group.
Unlike SBOM enforcement, CI and CD both use SlsaVerification (no separate CD step type).
Guide the user through a step-by-step interactive wizard (same UX as /generate-slsa):
- Wizard:
references/interactive-wizard-flow.md - UI ↔ YAML:
references/slsa-verification-step.md - CD containerized step groups:
skills/generate-slsa/references/cd-containerized-step-group.md
Interaction model (mandatory)
- One question per turn — use
AskQuestionwhen available; otherwise numbered options with(Recommended). - Opening message — add SLSA Verification; mention generation + optional policy prerequisites.
- Progress breadcrumb — after pipeline fetch:
Pipeline · Placement · Source · Details · Verify · Policy · Submit - Record answers — running summary; do not re-ask unless the user changes direction.
- Fetch before configure —
harness_getbefore placement/source questions. - Show pipeline structure — highlight
provenance(SLSA Generation) and connectors. - Infer source from generation — when one
provenancestep exists (oridentifier: slsageneration), reuse its source (maprepo→image_path, lowercase → PascalCase types). - Never guess image tags — default from generation step; ask if ambiguous.
- Confirm before write — summary +
harness_updateonly after user confirms. - Stop after update — after successful
harness_update, provide a configuration summary and point the user to/run-pipelineto execute. Do not callharness_execute, poll executions, or runharness_diagnosein this skill (same pattern as/configure-repo-scan). - CD on CI-only pipeline — do not reject CD verify; run Phase 3b to add Deploy stage + containerized group.
- Verify method must match generation — keyless ↔ keyless, keybased ↔ public key from same key pair.
What ships with it
2 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.
- 9d ago First seen · 306 lines · 173 tokens per session scan A 49511f99ded7
enforce-slsa is a skill published in the GitHub repository harness/harness-ai (19 stars, last pushed 18d ago), licensed Apache-2.0. It adds 173 tokens to every session and 3,098 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to enforce-slsa, differing in 0 lines, and is treated as a copy.
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