Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add SummerSec/SumSec-Skills/plugin install semantic-linterWrote 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/commands/summersec/sumsec-skills/stl-init)<a href="https://agentmods.dev/commands/summersec/sumsec-skills/stl-init"><img src="https://agentmods.dev/badge/commands/summersec/sumsec-skills/stl-init/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/commands/summersec/sumsec-skills/stl-init"><img src="https://agentmods.dev/badge/commands/summersec/sumsec-skills/stl-init.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 | $0.00012 | $0.00261 |
| Opus 5.5 | $0.00005 | $0.00104 |
| Sonnet 5.5 | $0.00002 | $0.00052 |
| Haiku 4.5 | $0.00001 | $0.00026 |
Grade A, and why
stl-init scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Semantic-Linter Init
Use this command to bootstrap project-local semantic rules.
Steps
- Treat the current working directory as the target project.
- Locate
scripts/build-rules.jsfrom one of these paths:${CODEX_PLUGIN_ROOT}/scripts/build-rules.js${CLAUDE_PLUGIN_ROOT}/scripts/build-rules.js./scripts/build-rules.js$HOME/.claude/plugins/semantic-linter/scripts/build-rules.js
- Run:
node "<SCRIPT>" --existing "$(pwd)"
- Tell the user which files were written:
semantic-rules.md- managed rules block in
AGENTS.mdand/orCLAUDE.md
- Explain the runtime behavior:
- Claude uses hooks plus the managed rules block.
- Codex uses the managed rules block in
AGENTS.md. - the default mode is
guarded - the project rules file is preferred over the plugin fallback
Notes
- Do not hand-write the managed rules block.
- Re-run
/stl-rulesafter lexicon or wording policy changes.
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.
- 1mo ago First seen · 36 lines · 12 tokens per session scan A 19cc10ee368f
stl-init is a command published in the GitHub repository SummerSec/SumSec-Skills (8 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 12 tokens to every session and 261 once invoked, about $0.0000 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 commands, from other repositories
revise-agents-md
Update AGENTS.md with learnings from this session.
hello-stranger
Say hello stranger.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.