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.
git clone --depth 1 https://github.com/Acheron-AI/angular-upgrade-kitWrote 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/agents/acheron-ai/angular-upgrade-kit/fixer)<a href="https://agentmods.dev/agents/acheron-ai/angular-upgrade-kit/fixer"><img src="https://agentmods.dev/badge/agents/acheron-ai/angular-upgrade-kit/fixer/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/agents/acheron-ai/angular-upgrade-kit/fixer"><img src="https://agentmods.dev/badge/agents/acheron-ai/angular-upgrade-kit/fixer.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 | $0.00029 | $0.00163 |
| Opus 5.5 | $0.00012 | $0.00065 |
| Sonnet 5.5 | $0.00006 | $0.00033 |
| Haiku 4.5 | $0.00003 | $0.00016 |
Grade A, and why
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 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
You are the build error fixer for an Angular project. You analyze compilation errors and apply targeted fixes.
What You Do
- Read the builder's error report from
upgrade/reports/ - Categorize errors (type errors, import errors, template errors, config errors)
- Fix errors in dependency order (shared modules first, then feature modules)
- Re-run build to verify fixes
- Write fix report to
upgrade/reports/fixer-vX-round-N.md
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 Changed · -64 lines · -29 tokens per session 107376aede15
- 1mo ago First seen · 87 lines · 58 tokens per session scan A 704e6c14f241
fixer is an agent published in the GitHub repository Acheron-AI/angular-upgrade-kit (1 stars, last pushed 1mo ago), licensed MIT. It adds 29 tokens to every session and 163 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 2026-08-31.
Other agents, from other repositories
bug-detector
Bug detection agent for CI: analyzes PR diffs for logic errors, null/undefined handling, race conditions, off-by-one errors, and edge cases. Uses git blame for historical context.
deep-reviewer
Deep review agent for CI: unconstrained code review that traces control flow across function and file boundaries, follows call sites, and catches cross-cutting bugs that specialist agents miss.
silent-failure-hunter
Error handling review agent for CI: identifies silent failures, empty catch blocks, swallowed errors, overly broad exception handling, and missing user feedback in PR diffs.
quality-fixer
Specialized agent for verifying software projects and fixing quality failures within the current task scope. Use proactively after code changes or for quality, test, build, lint, format, correctness, or fix requests.
doctrine-performance-optimizer
Read-only performance audit of Doctrine usage: N+1 queries, fetch modes, batch processing, missing indexes, and caching opportunities. Use proactively after adding entities, relations, repository queries, or when a page/endpoint is reported slow.
sniper
Use when: after ANY code modification (mandatory post-edit validation). Do NOT use for: new features, quick fixes already identified (use sniper-faster), read-only analysis.