Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/Benknightdark/neo-skillsnpx agentmods add skills/benknightdark/neo-skills/templatesWrote 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/benknightdark/neo-skills/templates)<a href="https://agentmods.dev/skills/benknightdark/neo-skills/templates"><img src="https://agentmods.dev/badge/skills/benknightdark/neo-skills/templates/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/benknightdark/neo-skills/templates"><img src="https://agentmods.dev/badge/skills/benknightdark/neo-skills/templates.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00047 | $0.00590 |
| Opus 5 | $0.00023 | $0.00295 |
| Sonnet 5 | $0.00009 | $0.00118 |
| Haiku 4.5 | $0.00005 | $0.00059 |
Grade A, and why
skill-name-kebab-case 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 11d 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 — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill Name
Briefly summarize the target task, scope, and expected outcome of this skill.
Gotchas
- Gotcha 1: [Describe a highly specific, non-obvious, environment-dependent pitfall that models are likely to hit, rather than generic advice].
- Gotcha 2: [e.g., database soft-deletes, multi-system field name mapping, or silent health checks].
Workflow Checklist
Progress:
- Step 1: Parse and Inventory (Load
references/schema.mdor executescripts/parse.py). - Step 2: Formulate Plan (Create a plan JSON and validate using
scripts/validate.py). - Step 3: Execute Task (Apply changes with idempotent actions).
- Step 4: Verify Results (Run tests and confirm output formatting).
Detailed Guidelines
Step 1 — Parse & Inventory
Instruct the agent how to analyze the environment:
- Load
references/guidelines.mdfor specific style rules. - Verify input arguments. If ambiguous, reject immediately with clear options.
Step 2 — Validation Loop
Instruct the agent to execute a deterministic loop to prevent broken output:
- Perform the edit.
- Validate using a validation script:
python3 scripts/validate.py "$TARGET_FILE" - If validation fails:
- Carefully inspect error codes and diagnostics in
stderr. - Revise target code/text.
- Run validation again.
- Carefully inspect error codes and diagnostics in
- Do NOT proceed to the next step until validation completely passes.
Step 3 — Plan-Validate-Execute
For batch, risky, or destructive actions:
- Extract data structures into a planning file
plan.json. - Compare plan fields against the schema.
- Validate:
python3 scripts/compare_schema.py plan.json references/schema.json - If valid, proceed with
--confirmor--force.
Output Templates
When presenting results, format exactly like this template:
# [Task Title]
## Executive Summary
[Brief description of changes made]
## Applied Checklist
- [x] Change 1
- [x] Change 2
## Recommendations / Next Steps
1. [First actionable step]
2. [Second actionable step]
What ships with it
3 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.
- 11d ago First seen · 77 lines · 47 tokens per session scan A 1c7558bc2e51
skill-name-kebab-case is a skill published in the GitHub repository Benknightdark/neo-skills (7 stars, last pushed 5d ago), licensed MIT. It adds 47 tokens to every session and 590 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 2026-08-31.
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