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/TechNickAI/ai-coding-configWrote 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/technickai/ai-coding-config/robustness-reviewer)<a href="https://agentmods.dev/agents/technickai/ai-coding-config/robustness-reviewer"><img src="https://agentmods.dev/badge/agents/technickai/ai-coding-config/robustness-reviewer/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/technickai/ai-coding-config/robustness-reviewer"><img src="https://agentmods.dev/badge/agents/technickai/ai-coding-config/robustness-reviewer.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 | $0.00028 | $0.02397 |
| Opus 5.5 | $0.00011 | $0.00959 |
| Sonnet 5.5 | $0.00006 | $0.00479 |
| Haiku 4.5 | $0.00003 | $0.00240 |
Grade A, and why
robustness-reviewer scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
const response = await fetch(url, { How it starts
The opening of the file, as written. The whole thing — 321 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Robustness Reviewer
Robust code handles the unexpected. It fails gracefully. It tells you when something's wrong. It doesn't rely on perfect conditions.
Type Safety
Review code to ensure TypeScript's protection is active throughout.
Robust code uses the type system fully. When types must be cast, robust code adds runtime validation that throws if the assumption was wrong. Robust code uses type guards and validation libraries like zod at boundaries.
Why this matters: Type casts allow invalid data to pass through unchecked. TypeScript only protects what it can see.
Error Handling
Review code to ensure errors reach monitoring and preserve context.
Robust code either re-throws exceptions or captures them to monitoring explicitly. Robust code preserves error context across async boundaries. Robust code uses typed errors with actionable messages.
Why this matters: Error monitoring only auto-captures unhandled exceptions. Users report bugs while dashboards show green when errors are caught without proper handling.
Key principle: "Fail Loud, Recover at Boundaries." Try/catch is only allowed for: retry logic, resource cleanup (finally), specific error type handling, background ops with monitoring, or UI graceful degradation with monitoring. Catch-log-return-null is banned.
Abstraction Health
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 · 321 lines · 28 tokens per session scan A 2d098c9ff28a
robustness-reviewer is an agent published in the GitHub repository TechNickAI/ai-coding-config (23 stars, last pushed 1mo ago), licensed MIT. It adds 28 tokens to every session and 2,397 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other agents, from other repositories
jd-fix-agent
You are a judgment-day surgical fix agent. Execute the fix instructions provided in the delegate prompt exactly.
ring:dead-code-reviewer
Dead Code Review: identifies code that became orphaned, unreachable, or unnecessary as a consequence of changes. Walks three concentric rings: target files, first-derivative dependents, and transitive ripple effect. Runs in parallel with other reviewers at Gate 8.
jd-fix-agent
Judgment Day surgical fix agent for confirmed findings. Can edit code and run focused tests.
sdd-remediate
Correct bound failed SDD evidence under one host-owned native attempt.
gentle-ai-explore
Read-only exploration and mapping for generic non-SDD work.
silent-failure-hunter
Use this agent when reviewing code changes in a pull request to identify silent failures, inadequate error handling, and inappropriate fallback behavior. This agent should be invoked proactively after completing a logical chunk of work that involves error handling, catch blocks, fallback logic, or any code that could…