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 causify-ai/helpers --skill coding.fix_inlinegit clone --depth 1 https://github.com/causify-ai/helpersWrote 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/causify-ai/helpers/coding.fix_inline)<a href="https://agentmods.dev/skills/causify-ai/helpers/coding.fix_inline"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/coding.fix_inline/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/causify-ai/helpers/coding.fix_inline"><img src="https://agentmods.dev/badge/skills/causify-ai/helpers/coding.fix_inline.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
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 →
- medium Excessive Agency · line 3 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
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 | $0.00009 | $0.00347 |
| Opus 5.5 | $0.00004 | $0.00139 |
| Sonnet 5.5 | $0.00002 | $0.00069 |
| Haiku 4.5 | $0.00001 | $0.00035 |
Grade A, and why
coding.fix_inline 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
-
I will pass you one or more files
<FILES> -
Look for functions that are too "thin", i.e., that call another function directly without doing much else
- E.g.,
python def cell1_plot_dag( G: nx.DiGraph, title: str, *, node_colors: Optional[Mapping[str, Any]] = None, edge_colors: Optional[Mapping[Tuple[str, str], Any]] = None, ax: Optional[maxes.Axes] = None, figsize: Optional[Tuple[int, int]] = None, pos: Optional[Dict] = None, dpi: int = hgraphviz.FIG_DPI, ) -> maxes.Axes: return hgraphviz.plot_causal_dag( G, title, mode="graphviz", node_colors=node_colors, edge_colors=edge_colors, ax=ax, figsize=figsize, dpi=dpi, )
- E.g.,
-
Ask the user if it's ok to remove them
-
Remove the functions and then look for all the invocations of the removed function and inline the called function
-
Read and apply to
<FILES>the rules from.claude/skills/coding.rules.md
Verification
- Confirm the user approved removal before any thin function is deleted
- Confirm every call site of a removed function is inlined correctly
- Confirm the code logic and behavior are unchanged
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 Changed · +5 lines ce5e8febe92a
- 1mo ago First seen · 41 lines · 9 tokens per session scan A 1dc47aa5f700
coding.fix_inline is a skill published in the GitHub repository causify-ai/helpers (150 stars, last pushed yesterday), licensed Apache-2.0. It adds 9 tokens to every session and 347 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 2026-08-30.
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