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 agentmods add skills/rse/ase/ase-code-lintnpx skills add rse/ase --skill ase-code-lintgit clone --depth 1 https://github.com/rse/aseWhat 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 | $0.00030 | $0.05348 |
| Opus 5 | $0.00015 | $0.02674 |
| Sonnet 5 | $0.00006 | $0.01070 |
| Haiku 4.5 | $0.00003 | $0.00535 |
Grade A, and why
ase-code-lint scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 513 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@${CLAUDE_SKILL_DIR}/../../meta/ase-control.md @${CLAUDE_SKILL_DIR}/../../meta/ase-skill.md @${CLAUDE_SKILL_DIR}/../../meta/ase-dialog.md @${CLAUDE_SKILL_DIR}/../../meta/ase-getopt.md
$ARGUMENTS
-
The project source artifacts are classified as a black box, so the user does not want them inspected or their problems surfaced. Skip the entire investigation and reporting: do not invoke any
GloborAgenttool and do not read any source, only output the following and then SKIP the remaining steps STEP 2 and STEP 3:First, determine the effective aspect set , i.e., the code quality aspects which are checked at all. For this, parse and as comma-separated token lists, silently dropping the
nonesentinel and any empty token. If a token is not one of the aspect idsA01...A21, only output the following and then STOP the entire flow (do not perform any further steps):Otherwise set to all twenty-one aspect ids
A01...A21if both lists are empty, to the include list if only it is non-empty, to all twenty-one minus the exclude list if only it is non-empty, and to the include list minus the exclude list if both are non-empty. If the resulting is empty, only output the following and then STOP the entire flow (do not perform any further steps):Then, use the following to give a hint on this step:
Dispatch the investigation to sub-agents via the
Agenttool so that no investigation details leak into the user-visible transcript. The sub-agents perform the silent reading and checking; only their final structured return values are consumed here.For this, first silently resolve
<getopt-arguments/>to the list of individual source code files, expanding any directory or wildcard references with theGlobtool. Then partition , preserving order, into at most eight batches of roughly equal size (a single file yields a single batch), and invoke the following tool once per batch, emitting all invocations in one single message so they run in parallel:Agent( description: "Lint Investigation (<batch-index/>/<batch-count/>)", subagent_type: "ase:ase-code-lint", prompt: "<aspects/> <batch/>", run_in_background: false )Here is the comma-separated list of the effective aspect ids (without any spaces), is the space-separated list of the source code file paths of the corresponding batch, is the 1-based index of that batch, and is the total number of batches, so that each parallel invocation is distinguishable in the progress display.
What ships with it
1 file 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.
- 2d ago First seen · 513 lines · 30 tokens per session scan A cc9471b35c58
ase-code-lint is a skill published in the GitHub repository rse/ase (47 stars, last pushed 5d ago), licensed Apache-2.0. It adds 30 tokens to every session and 5,348 once invoked, about $0.0002 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 2026-08-30.
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