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 agentmods add commands/kensaurus/cursor-kenji/fix-issuegit clone --depth 1 https://github.com/kensaurus/cursor-kenjiWhat 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 | $0.00021 | $0.00714 |
| Opus 5 | $0.00010 | $0.00357 |
| Sonnet 5 | $0.00004 | $0.00143 |
| Haiku 4.5 | $0.00002 | $0.00071 |
Grade A, and why
fix-issue 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 2d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fix-issue
Fix GitHub Issue
Fetch a GitHub issue, understand it, find the relevant code, implement the fix, verify, and open a PR.
Step 1: Fetch Issue Details
gh issue view <number> --json title,body,labels,assignees,comments
Extract:
- What the issue is about
- Steps to reproduce (if bug)
- Expected behavior
- Any labels (bug, feature, enhancement)
Step 2: Find Relevant Code
Use the issue title and description to search the codebase:
SemanticSearch(query: "<issue description summarized as a question>", target_directories: [])
Also try targeted searches:
Grep(pattern: "<key symbol or error message from the issue>")
Read all relevant files fully before making changes.
Step 3: Implement the Fix
- Follow existing patterns in the codebase
- Keep changes minimal and focused on the issue
- If the fix touches UI, ensure design system tokens are used
- If the fix touches text, ensure i18n
t()keys are used
Step 4: Verify
4a. Lint
ReadLints(paths: [<list of changed files>])
Fix any lint errors introduced.
4b. Build
npm run build
4c. Test
npm run test:unit
If a relevant test file exists, run it specifically:
npx vitest run <path/to/related.test.ts>
4d. Sentry Check (if available)
Search for related Sentry issues in the changed module:
sentry:search_issues
{
"organizationSlug": "<ORG_SLUG>",
"projectSlug": "<PROJECT_SLUG>",
"query": "is:unresolved <module_keyword>"
}
Step 5: Commit
git add <changed files>
git commit -m "$(cat <<'EOF'
fix(<scope>): <short description>
<body explaining why, not what>
Fixes #<number>
EOF
)"
Step 6: Push and Open PR
git push -u origin HEAD
gh pr create --title "fix(<scope>): <short description>" --body "$(cat <<'EOF'
## Summary
Fixes #<number>
<1-3 bullet points explaining the change>
## Test plan
- [ ] Build passes
- [ ] Lint passes
- [ ] Unit tests pass
- [ ] Manual verification of the fix
EOF
)"
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.
- 2d ago First seen · 148 lines · 21 tokens per session scan A b1179e8cb2e6
fix-issue is a command published in the GitHub repository kensaurus/cursor-kenji (9 stars, last pushed 4d ago), licensed MIT. It adds 21 tokens to every session and 714 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 2026-08-31.
Other commands, from other repositories
commit-msg
Cursor tooling: skills, rules, subagents.
boot
Initialize agent, verify setup, and load rules.
code-review
Confidence-based code review checklist.
prp-new
Create new Product Requirement Prompt from scratch.
clean
Repository hygiene — clean temp files, organize execution folders.
context
Dynamic context management — status, clean, log, save, read.