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 helmedeiros/clean-code-skills --skill fp-error-handlinggit clone --depth 1 https://github.com/helmedeiros/clean-code-skillsWrote 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/helmedeiros/clean-code-skills/fp-error-handling)<a href="https://agentmods.dev/skills/helmedeiros/clean-code-skills/fp-error-handling"><img src="https://agentmods.dev/badge/skills/helmedeiros/clean-code-skills/fp-error-handling.svg" alt="Measured on agentmods" 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 | $0.00054 | $0.00845 |
| Opus 5 | $0.00027 | $0.00423 |
| Sonnet 5 | $0.00011 | $0.00169 |
| Haiku 4.5 | $0.00005 | $0.00085 |
Grade A, and why
fp-error-handling 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 7d 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 — 92 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FP: Functional Error Handling
Handle errors using Result, Either, and Option types instead of exceptions, making error paths explicit, composable, and impossible to ignore.
When This Skill Applies
- Try-catch blocks are scattered throughout the codebase
- Functions return null to indicate failure (null is ambiguous)
- Error handling is inconsistent or often forgotten
- The user mentions Result, Either, Option, Maybe, or functional error handling
- Thrown exceptions are used for control flow, not exceptional situations
Core Principle
Exceptions are invisible in type signatures and easy to forget. Returning typed error values (Result, Either, Option) makes failure an explicit part of the function's contract. The caller must handle the error case — the type system enforces it. This creates self-documenting code where error paths are visible and composable.
Workflow
Step 1: Identify Error-Prone Functions
Find functions that throw exceptions, return null/undefined on failure, or use boolean success flags. These are candidates for typed error handling.
Step 2: Choose the Right Type
- Option/Maybe: the value may or may not exist (no error details needed).
- Result/Either: the operation may succeed or fail with an error value.
Step 3: Replace Exceptions with Return Types
Change the function signature to return Result<Value, Error> instead of throwing. The caller pattern-matches or chains on the result.
Step 4: Compose Operations
Chain multiple fallible operations using map, flatMap/chain, and mapError. Each step transforms the success value while preserving the error path.
Step 5: Handle at the Boundary
Convert typed errors to exceptions or HTTP responses at the system boundary (API handler, main function). Keep the domain pure.
Detection / Indicators
- Try-catch used for business logic flow control
- Functions that return
nullto mean "not found" or "failed" - Boolean return values for success/failure:
if (!save(data)) { ... } - Inconsistent error handling: some callers catch, others do not
- Deeply nested try-catch blocks
- Caught exceptions immediately re-thrown or logged and swallowed
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 7d ago First seen · 92 lines · 54 tokens per session scan A 8a1cb4ca2332
fp-error-handling is a skill published in the GitHub repository helmedeiros/clean-code-skills (2 stars, last pushed 6mo ago), licensed MIT. It adds 54 tokens to every session and 845 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.
Other skills, from other repositories
codex-setup
Initialize sd0x-dev-flow infrastructure for Codex CLI and other non-Claude agents. Generates AGENTS.md, installs the commit-msg hook, copies runner scripts. The pre-push gate is opt-in via --with-push-gate. Use when setting up a new project or after updating skills.
recap-doc
Post-development recap document generator. Use when: AI/Codex has implemented a feature and the user needs a guided walkthrough of what changed and why, with blind-spot detection and anticipated questions. Not for: Q&A follow-up (use /recap-ask), technical share-out for teammates (use /tech-brief), or generic code…
runbook
Generate and update feature release runbooks from existing docs and codebase. Use when: creating operational runbook, release handbook, deployment checklist, pre-release preparation. Not for: incident response (v2), code review (use codex-code-review), architecture design (use architecture).
test-review
Test coverage review via Codex exec. Use when: reviewing test sufficiency, identifying coverage gaps, test quality audit. Not for: generating tests (use codex-test-gen), code review (use codex-code-review). Output: coverage analysis + gap report.
debug
Interactive debugging workflow with hypothesis-driven probe loop. Use when: unknown bugs, script errors, silent failures, troubleshooting. Not for: known bugs (use bug-fix), GitHub issue analysis (use issue-analyze), code understanding (use code-explore). Output: debug report with probe journal + root cause + fix.
feature-dev
Feature development workflow. Use when: implementing features, writing code, running dev loop. Not for: understanding code (use code-explore), reviewing code (use codex-code-review). Output: implemented feature + tests + review gate.