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 agentmods add skills/supersynergy/awesome-agentic-coding/search-codenpx skills add Supersynergy/awesome-agentic-coding --skill search-codegit clone --depth 1 https://github.com/Supersynergy/awesome-agentic-codingWhat 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 | $0.00024 | $0.00539 |
| Opus 5 | $0.00012 | $0.00269 |
| Sonnet 5 | $0.00005 | $0.00108 |
| Haiku 4.5 | $0.00002 | $0.00054 |
Grade A, and why
search-code 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 yesterday.
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
Deep Code Search
Search the codebase for: $ARGUMENTS
Strategy (escalating depth)
Level 1: Direct Search (try first)
Grep for exact pattern → if found, return results
Glob for file patterns → if found, read relevant files
Level 2: Semantic Search (if Level 1 fails)
Try related terms:
- Synonyms: "auth" → "login", "session", "token", "jwt"
- Abbreviations: "config" → "cfg", "conf", "settings"
- Naming conventions: camelCase, snake_case, kebab-case variants
Level 3: Structural Search (if Level 2 fails)
Spawn a Haiku researcher agent to:
- Find all entry points (main files, route handlers, exports)
- Trace the call chain to the target functionality
- Map the dependency graph
Common Search Patterns
| Looking for | Search with |
|---|---|
| API routes | Grep("app\.(get|post|put|delete)") or Grep("router\.") |
| React components | Glob("src/**/*.tsx") + Grep("export.*function|export default") |
| Database queries | Grep("\.query|\.select|\.insert|\.update|\.delete") |
| Auth checks | Grep("auth|middleware|session|token|jwt") |
| Error handling | Grep("catch|throw|Error|error") |
| Environment vars | Grep("process\.env|import\.meta\.env|Deno\.env") |
| Test files | Glob("**/*.{test,spec}.{ts,tsx,js,jsx}") |
| Config files | Glob("**/*.{config,rc}.{ts,js,json,yml,yaml}") |
Output Format
Return:
- File path + line number
- Relevant code snippet (5-10 lines, not full file)
- Brief explanation of what it does
- Related files (if part of a larger pattern)
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.
- yesterday First seen · 51 lines · 24 tokens per session scan A 903979c80d92
search-code is a skill published in the GitHub repository Supersynergy/awesome-agentic-coding (1 stars, last pushed 1mo ago), licensed MIT. It adds 24 tokens to every session and 539 once invoked, about $0.0001 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
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aiwiki-privacy-entry-author
为 AiWiki「LLM 隐私保护」主题撰写或修订一条攻防条目（privacy/ 下的 .mdx）。当需要新增/改写隐私条目、并保证第一人称红线、九节结构、三道硬闸门、隐私 frontmatter 与一手出处时使用。.
aiwiki-research-refresh
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aiwiki-entry-author
为 AiWiki 撰写或修订一条「误区」条目（docs/ 下的 .mdx）。当需要新增/改写误区条目、并保证第一人称 AI 声音、七段结构、frontmatter 规范与可核查出处时使用。.
aiwiki-translator
把一条 AiWiki 中文误区条目（docs/ 下的 .mdx）翻译成英文镜像，输出到 i18n/en/ 对应路径。当需要为新增或修订的中文条目生成/更新英文版时使用。.
issue-triage
Issue triage: audit open issues, categorize, detect duplicates, cross-ref PRs, risk assessment, post comments. Args: "all" for deep analysis of all, issue numbers to focus (e.g. "42 57"), "en"/"fr" for language, no arg = audit only in French.