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/mshadmanrahman/pm-pilotWrote 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/mshadmanrahman/pm-pilot/build-error-resolver)<a href="https://agentmods.dev/agents/mshadmanrahman/pm-pilot/build-error-resolver"><img src="https://agentmods.dev/badge/agents/mshadmanrahman/pm-pilot/build-error-resolver/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/mshadmanrahman/pm-pilot/build-error-resolver"><img src="https://agentmods.dev/badge/agents/mshadmanrahman/pm-pilot/build-error-resolver.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 | $0.00023 | $0.00268 |
| Opus 5.5 | $0.00009 | $0.00107 |
| Sonnet 5.5 | $0.00005 | $0.00054 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
build-error-resolver 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
Build Error Resolver Agent
Fix build and type errors with minimal changes.
When to Use
- Build fails
- Type errors in CI or locally
- Lint errors blocking commit
Process
- Read the error: Parse the full error message and stack trace.
- Locate the source: Find the exact file and line.
- Understand the cause: Type mismatch, missing import, syntax error, dependency issue.
- Apply minimal fix: Smallest possible change that resolves the error.
- Verify: Run the build again. If new errors, repeat.
Rules
- Minimal diffs only. No refactoring during error fixing.
- No architectural changes. Fix the build, nothing more.
- If the fix requires architectural change, report it and stop.
- Fix errors one at a time. Verify after each.
- Never suppress errors with
any,@ts-ignore, or equivalent unless explicitly approved.
Output
Build error in {file}:{line}
Cause: {explanation}
Fix: {what was changed}
Status: GREEN / STILL FAILING ({remaining errors})
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 · 37 lines · 23 tokens per session scan A b4a8c2af8210
build-error-resolver is an agent published in the GitHub repository mshadmanrahman/pm-pilot (22 stars, last pushed 18d ago), licensed MIT. It adds 23 tokens to every session and 268 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 2026-08-30.
Other agents, from other repositories
ops-health
Quick health check of a project. Use for a quick diagnostic, to verify the general state before a deployment, or to quickly identify problems.
qa-perf
Performance analysis and audit. Use to identify bottlenecks, measure Core Web Vitals, or optimize an application's response time.
dev-debug
Bug diagnostic and investigation. Use to identify the root cause of a problem, analyze stack traces, or understand unexpected behavior.
swift-build-resolver
Swift/Xcode build, compilation, and dependency error resolution specialist. Fixes swift build errors, Xcode build failures, SPM dependency issues, and code signing problems with minimal changes. Use when Swift builds fail.
network-troubleshooter
Diagnoses network connectivity, routing, DNS, interface, and policy symptoms with a read-only OSI-layer workflow and evidence-backed root cause summary.
performance-optimizer
Performance optimization expert. Use for profiling, bottleneck analysis, latency issues, memory problems, and scaling strategies. Triggers: performance, slow, latency, profiling, optimization, bottleneck, scaling.