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/madappgang/claude-code/search-interceptornpx skills add MadAppGang/claude-code --skill search-interceptorgit clone --depth 1 https://github.com/MadAppGang/claude-codeWrote 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/madappgang/claude-code/search-interceptor)<a href="https://agentmods.dev/skills/madappgang/claude-code/search-interceptor"><img src="https://agentmods.dev/badge/skills/madappgang/claude-code/search-interceptor.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 | $0.00039 | $0.01362 |
| Opus 5 | $0.00019 | $0.00681 |
| Sonnet 5 | $0.00008 | $0.00272 |
| Haiku 4.5 | $0.00004 | $0.00136 |
Grade A, and why
search-interceptor 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 4d 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 — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Search Interceptor
This skill helps optimize bulk file operations by suggesting semantic search alternatives when they would be more efficient.
When Semantic Search is More Efficient
| Scenario | Token Cost | Alternative |
|---|---|---|
| Read 5+ files | ~5000 tokens | claudemem search (~500 tokens) |
| Glob all *.ts files | ~3000+ tokens | claudemem --agent map |
| Sequential reads to understand | Variable | One semantic query |
When to Consider Alternatives
Multiple File Reads
If planning to read several files, consider:
# Instead of reading 5 files individually
claudemem search "concept from those files" -n 15
# Gets ranked results with context
Broad Glob Patterns
If using patterns like src/**/*.ts:
# Instead of globbing and reading all matches
claudemem --agent map "what you're looking for"
# Gets structural overview with PageRank ranking
File Paths Mentioned in Task
Even when specific paths are mentioned, semantic search often finds additional relevant code:
claudemem search "concept related to mentioned files"
Interception Protocol
Step 1: Pause Before Execution
When you're about to execute bulk file operations, STOP and run:
claudemem status
Step 2: Evaluate
If claudemem is indexed:
| Your Plan | Better Alternative |
|---|---|
| Read 5 auth files | claudemem search "authentication login session" |
| Glob all services | claudemem search "service layer business logic" |
| Read mentioned paths | claudemem search "[concept from those paths]" |
If claudemem is NOT indexed:
claudemem index -y
Then proceed with semantic search.
Step 3: Execute Better Alternative
# Instead of reading N files, run ONE semantic query
claudemem search "concept describing what you need" -n 15
# ONLY THEN read specific lines from results
Interception Decision Matrix
| Situation | Intercept? | Action |
|---|---|---|
| Read 1-2 specific files | No | Proceed with Read |
| Read 3+ files in investigation | YES | Convert to claudemem search |
| Glob for exact filename | No | Proceed with Glob |
| Glob for pattern discovery | YES | Convert to claudemem search |
| Grep for exact string | No | Proceed with Grep |
| Grep for semantic concept | YES | Convert to claudemem search |
| Files mentioned in prompt | YES | Search semantically first |
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.
- 4d ago First seen · 214 lines · 39 tokens per session scan A c8d3252e9321
search-interceptor is a skill published in the GitHub repository MadAppGang/claude-code (279 stars, last pushed 5mo ago), licensed MIT. It adds 39 tokens to every session and 1,362 once invoked, about $0.0002 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…