Borrowing it
Nothing to install: this file belongs to anortham/julie. 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/anortham/julie/main/.claude/skills/search-debug/SKILL.mdgit clone --depth 1 https://github.com/anortham/julieWrote 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/anortham/julie/search-debug)<a href="https://agentmods.dev/skills/anortham/julie/search-debug"><img src="https://agentmods.dev/badge/skills/anortham/julie/search-debug/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/anortham/julie/search-debug"><img src="https://agentmods.dev/badge/skills/anortham/julie/search-debug.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 | $0.00033 | $0.01209 |
| Opus 5.5 | $0.00013 | $0.00484 |
| Sonnet 5.5 | $0.00007 | $0.00242 |
| Haiku 4.5 | $0.00003 | $0.00121 |
Grade A, and why
search-debug 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- search-debug — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Search Debug
Diagnose why a Julie search returns unexpected results. Use this when a search misses an expected symbol, ranks it too low, or returns irrelevant results. This skill is for Julie dogfooding, not general plugin usage.
Process
Step 1: Reproduce the Search
Run the exact search the user reported:
fast_search(query="<original_query>", limit=20, workspace="<workspace_id>")
fast_search returns mixed-kind results; each hit carries kind. Note what comes back, the top results, their scores, and what's missing. If the default response says "No lexical results. Showing semantic fallback candidates.", treat that as a semantic rescue, not a lexical hit.
If the report involves backend behavior, run the exact requested backend and compare backend="lexical", backend="semantic", and backend="hybrid". Explicit lexical stays pure lexical for bakeoffs; semantic and hybrid are symbol-only concept search.
Step 2: Verify the Expected Symbol Exists
Search for the expected symbol directly:
fast_search(query="<expected_symbol_name>", workspace="<workspace_id>")
If it doesn't appear at all, the symbol may not be indexed.
Step 3: Check Index Health
manage_workspace(operation="health", workspace_id="<workspace_id>", detailed=true)
Look for:
- Is the workspace indexed?
- Are there indexing errors?
- Is the file containing the expected symbol in the indexed file list?
Step 4: Deep Dive the Expected Symbol
deep_dive(symbol="<expected_symbol>", depth="context", workspace="<workspace_id>")
Check:
- Centrality: Low-centrality symbols get less boost in search results. Symbols with no references won't benefit from centrality boosting. Use
get_contextto see the centrality label (low/medium/high). - Symbol kind: Is it a function, struct, variable? Variables and constants may score differently.
- File path: Is it in a test/docs/fixture path? Docs/tests get
NL_PATH_PENALTY_DOCS/NL_PATH_PENALTY_TESTS(0.95x); fixture paths get a steeperNL_PATH_PENALTY_FIXTURES(0.75x). - Name shape: Does the symbol name break into the tokens the query implies?
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 Changed d11df0ed22cf
- 2mo ago First seen · 115 lines · 33 tokens per session scan A 6b75ca072491
search-debug is a skill published in the GitHub repository anortham/julie (6 stars, last pushed 27d ago), licensed MIT. It adds 33 tokens to every session and 1,209 once invoked, about $0.0001 per session on Opus 5.5. 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.
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