credit-note-fixer

A focused repair procedure for a small credit-note shell-script bug. A credit note is a document that records money credited back to a customer.

In plain words
What is it for?
Use it to inspect the specified script and test, make the smallest correction, and run the exact targeted shell test.
Why use it?
It keeps the fix narrow and verifies that the output still uses the required label and a positive amount.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/openai/openai-agents-python/credit-note-fixer
Any agent
npx skills add openai/openai-agents-python --skill credit-note-fixer
Clone the repo
git clone --depth 1 https://github.com/openai/openai-agents-python

Made for: Claude Code, Codex.

Per session 21 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 152 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00021 $0.00152
Opus 5 $0.00010 $0.00076
Sonnet 5 $0.00004 $0.00030
Haiku 4.5 $0.00002 $0.00015

Measured 3d ago against content hash f3b62900c2f5, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

credit-note-fixer 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 3d 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.

examples/sandbox/docs/skills/credit-note-fixer/SKILL.md · 15 lines

What it actually says

Credit Note Fixer

Follow this workflow:

  1. Read repo/task.md.
  2. Inspect repo/credit_note.sh and repo/tests/test_credit_note.sh.
  3. Make the smallest correct change that keeps the output label as credit and the amount positive. If you use apply_patch, use workspace-root-relative paths such as repo/credit_note.sh and repo/tests/test_credit_note.sh.
  4. Run exactly sh tests/test_credit_note.sh from repo/.
  5. In the final answer, summarize the bug, the fix, and the exact verification command.
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.

  1. 3d ago First seen · 15 lines · 21 tokens per session scan A f3b62900c2f5

Subscribe to this mod's changes

credit-note-fixer is a skill published in the GitHub repository openai/openai-agents-python (29,123 stars, last pushed yesterday), licensed MIT. It adds 21 tokens to every session and 152 once invoked, about $0.0001 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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