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 kgiwojno/g-sdd --skill g-fixgit clone --depth 1 https://github.com/kgiwojno/g-sddWrote 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/kgiwojno/g-sdd/g-fix)<a href="https://agentmods.dev/skills/kgiwojno/g-sdd/g-fix"><img src="https://agentmods.dev/badge/skills/kgiwojno/g-sdd/g-fix/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/kgiwojno/g-sdd/g-fix"><img src="https://agentmods.dev/badge/skills/kgiwojno/g-sdd/g-fix.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00055 | $0.04404 |
| Opus 5 | $0.00028 | $0.02202 |
| Sonnet 5 | $0.00011 | $0.00881 |
| Haiku 4.5 | $0.00006 | $0.00440 |
Grade A, and why
g-fix 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 10d 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 — 494 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Behavior
1. Collect bug descriptions
Ask the user to describe the bugs they want to fix. They may provide one or multiple bugs at once.
For each bug, capture:
- Description: what's wrong (symptoms, expected vs actual)
- Steps to reproduce: if the user provides them
Number the bugs as they're described (Bug 1, Bug 2, etc.).
When collecting bug descriptions, apply the four interview
disciplines below to sharpen the wording against the
project's canonical vocabulary — bug reports phrased in
fuzzy terms produce fuzzy fixes. The disciplines apply to
bug descriptions in place of feature decisions; the text
itself is identical to the discipline block used by
/g-prd step 6 and /g-plan step 4.
Apply four interview disciplines
During the interview, actively apply these four behaviors. They are additive to the existing question-by-question interview structure, not a replacement.
-
Challenge against the glossary. When the user uses a term that conflicts with the existing CONTEXT.md (or a project's domain-specific convention), call it out immediately. "Your glossary defines 'cancellation' as X, but you seem to mean Y — which is it?"
-
Sharpen fuzzy language. When the user uses vague or overloaded terms, propose a precise canonical term and inline-write it to CONTEXT.md once resolved. "You're saying 'account' — do you mean the Customer or the User? Those are different things." After resolution, update CONTEXT.md in the same turn — do not batch up glossary edits to end-of-interview.
-
Discuss concrete scenarios. When domain relationships are being discussed, stress-test them with invented edge-case scenarios. Force the user to be precise about the boundaries between concepts.
-
Cross-reference with code. When the user states how something works, check whether the code agrees. If you find a contradiction, surface it: "Your code cancels entire Orders, but you just said partial cancellation is possible — which is right?"
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.
- 10d ago First seen · 494 lines · 55 tokens per session scan A abbd89d1594b
g-fix is a skill published in the GitHub repository kgiwojno/g-sdd (6 stars, last pushed 2mo ago), licensed MIT. It adds 55 tokens to every session and 4,404 once invoked, about $0.0003 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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