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 ashutoshsinghpr7/wikiskill --skill spec-literal-executiongit clone --depth 1 https://github.com/ashutoshsinghpr7/wikiskillWrote 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/ashutoshsinghpr7/wikiskill/spec-literal-execution)<a href="https://agentmods.dev/skills/ashutoshsinghpr7/wikiskill/spec-literal-execution"><img src="https://agentmods.dev/badge/skills/ashutoshsinghpr7/wikiskill/spec-literal-execution/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/ashutoshsinghpr7/wikiskill/spec-literal-execution"><img src="https://agentmods.dev/badge/skills/ashutoshsinghpr7/wikiskill/spec-literal-execution.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 | $0.00033 | $0.00398 |
| Opus 5.5 | $0.00013 | $0.00159 |
| Sonnet 5.5 | $0.00007 | $0.00080 |
| Haiku 4.5 | $0.00003 | $0.00040 |
Grade A, and why
spec-literal-execution 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
Spec Literal Execution — no unstated transforms
Problem
An exact-match grader rejected output.txt (score 0.0) although the agent
believed it followed every spec clause and even re-read the file.
Root cause
Spec says "one line per product with quantity > 0" and never mentions
aggregation, yet the agent inferred "product = unique product name" and
summed duplicate rows (cherry 20+2 → 22, elderberry 11+6 → 17). The grader
treats each JSON object as its own product row: CHERRY;20 and CHERRY;2
must be separate lines. The added transformation — not the arithmetic or
tooling — caused the failure.
Fix
- Apply ONLY the clauses literally present in the spec. Each input record maps to its own output line unless the spec explicitly says otherwise.
- Never add aggregation, dedup, rounding, or case changes "for cleanliness".
- If a spec filter (e.g.
qty >= 10) is the only thing removing duplicates, apply it per row — do not aggregate first.
Evidence
- FAIL: spec-format2-1 (0.0). PASS: spec-format1-1, spec-format3-1 (1.0) — same duplicate-shaped data; the passing runs filtered per row with no aggregation.
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 · 42 lines · 33 tokens per session scan A 19cb4871f5f2
spec-literal-execution is a skill published in the GitHub repository ashutoshsinghpr7/wikiskill (277 stars, last pushed 1mo ago), licensed MIT. It adds 33 tokens to every session and 398 once invoked, about $0.0001 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 2026-09-05.
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