Borrowing it
Nothing to install: this file belongs to kissrosecicd-hub/agents-evolution. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/kissrosecicd-hub/agents-evolution/main/.agents/skills/tob-sharp-edges/SKILL.mdgit clone --depth 1 https://github.com/kissrosecicd-hub/agents-evolutionWrote 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/kissrosecicd-hub/agents-evolution/tob-sharp-edges)<a href="https://agentmods.dev/skills/kissrosecicd-hub/agents-evolution/tob-sharp-edges"><img src="https://agentmods.dev/badge/skills/kissrosecicd-hub/agents-evolution/tob-sharp-edges/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/skills/kissrosecicd-hub/agents-evolution/tob-sharp-edges"><img src="https://agentmods.dev/badge/skills/kissrosecicd-hub/agents-evolution/tob-sharp-edges.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 | $0.00074 | $0.02515 |
| Opus 5.5 | $0.00030 | $0.01006 |
| Sonnet 5.5 | $0.00015 | $0.00503 |
| Haiku 4.5 | $0.00007 | $0.00251 |
Grade A, and why
sharp-edges 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.
This is a copy
88% identical to sharp-edges — 11 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 293 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sharp Edges Analysis
Evaluates whether APIs, configurations, and interfaces are resistant to developer misuse. Identifies designs where the "easy path" leads to insecurity.
When to Use
- Reviewing API or library design decisions
- Auditing configuration schemas for dangerous options
- Evaluating cryptographic API ergonomics
- Assessing authentication/authorization interfaces
- Reviewing any code that exposes security-relevant choices to developers
When NOT to Use
- Implementation bugs (use standard code review)
- Business logic flaws (use domain-specific analysis)
- Performance optimization (different concern)
Core Principle
The pit of success: Secure usage should be the path of least resistance. If developers must understand cryptography, read documentation carefully, or remember special rules to avoid vulnerabilities, the API has failed.
Rationalizations to Reject
| Rationalization | Why It's Wrong | Required Action |
|---|---|---|
| "It's documented" | Developers don't read docs under deadline pressure | Make the secure choice the default or only option |
| "Advanced users need flexibility" | Flexibility creates footguns; most "advanced" usage is copy-paste | Provide safe high-level APIs; hide primitives |
| "It's the developer's responsibility" | Blame-shifting; you designed the footgun | Remove the footgun or make it impossible to misuse |
| "Nobody would actually do that" | Developers do everything imaginable under pressure | Assume maximum developer confusion |
| "It's just a configuration option" | Config is code; wrong configs ship to production | Validate configs; reject dangerous combinations |
| "We need backwards compatibility" | Insecure defaults can't be grandfather-claused | Deprecate loudly; force migration |
Sharp Edge Categories
1. Algorithm/Mode Selection Footguns
APIs that let developers choose algorithms invite choosing wrong ones.
The JWT Pattern (canonical example):
- Header specifies algorithm: attacker can set
"alg": "none"to bypass signatures - Algorithm confusion: RSA public key used as HMAC secret when switching RS256→HS256
- Root cause: Letting untrusted input control security-critical decisions
What ships with it
16 files 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.
- references/auth-patterns.md 6.8 KB
- references/case-studies.md 8.0 KB
- references/config-patterns.md 9.5 KB
- references/crypto-apis.md 5.2 KB
- references/lang-c.md 5.5 KB
- references/lang-csharp.md 7.2 KB
- references/lang-go.md 6.5 KB
- references/lang-java.md 6.7 KB
- references/lang-javascript.md 6.8 KB
- references/lang-kotlin.md 6.6 KB
- references/lang-php.md 6.0 KB
- references/lang-python.md 6.5 KB
- references/lang-ruby.md 6.1 KB
- references/lang-rust.md 6.4 KB
- references/lang-swift.md 6.1 KB
- references/language-specific.md 13 KB
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 · 293 lines · 74 tokens per session scan A 38e1aca2a418
sharp-edges is a skill published in the GitHub repository kissrosecicd-hub/agents-evolution (31 stars, last pushed 6mo ago), licensed MIT. It adds 74 tokens to every session and 2,515 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 88% identical to sharp-edges, differing in 11 lines, and is treated as a copy.
Other skills, from other repositories
autoreview
Structured code review through the shared OpenClaw agent-skills installation.
omh-code-review
This is an OMH code-review workflow skill, projected for Agent Skills hosts (Claude Code, Codex, Cursor, opencode, OpenClaw, pi).
revdiff-plan
Review the last Codex assistant message (plan, analysis, or proposal) with inline annotations in a TUI overlay. Extracts the most recent response from Codex rollout files and opens it in revdiff for review and annotation. Activates on "revdiff-plan", "review plan with revdiff", "annotate plan", "review last response"…
explore-unknowns
Guide the user through a quadrant walk that maps the unknowns of a task — open by listing the known knowns, then work through known unknowns, unknown knowns, and unknown unknowns one stage at a time, ending with a complete four-quadrant map in the user's hands. Use when a request is ambiguous or underspecified, the…
asplos-writing-style
Use when drafting or revising ASPLOS prose — engineering the first two pages that rapid review actually reads, stating the cross-layer insight as one quotable sentence, structuring per-layer mechanism sections, writing bounded claims, and fitting everything into 11 self-contained pages that include figures and…
re0-merge
Review and land an external contribution the way this suite does: gate it against the thesis, land it with the author's credit intact, complete a new skill rather than merging it raw, then approve, credit, and explain before closing. Use when reviewing a pull request, as any collaborator or maintainer, not only the…