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 anortham/julie-plugin --skill explore-areagit clone --depth 1 https://github.com/anortham/julie-pluginWrote 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-plugin/explore-area)<a href="https://agentmods.dev/skills/anortham/julie-plugin/explore-area"><img src="https://agentmods.dev/badge/skills/anortham/julie-plugin/explore-area/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-plugin/explore-area"><img src="https://agentmods.dev/badge/skills/anortham/julie-plugin/explore-area.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 | $0.00049 | $0.01602 |
| Opus 5.5 | $0.00020 | $0.00641 |
| Sonnet 5.5 | $0.00010 | $0.00320 |
| Haiku 4.5 | $0.00005 | $0.00160 |
Grade A, and why
explore-area 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
100% identical to explore-area — 0 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Explore Area
Orient on an unfamiliar area of the codebase using Julie's get_context tool. This is the recommended starting point before any modification task — understand the area first, then dive in.
Process
Step 1: Get Token-Budgeted Context
get_context(query="<area, concept, or module name>", workspace="<workspace_id>")
Conceptual queries work well here, not just symbol names. For example, get_context(query="error handling and retries", workspace="<workspace_id>") will find relevant symbols by meaning via semantic search.
For a quick concept-to-symbol probe before expanding context, use fast_search(query="...", backend="semantic", workspace="<workspace_id>") or backend="hybrid". Those backends return symbol-backed hits only; use explicit backend="lexical" for file names, path fragments, or pure lexical comparison. Omitting backend runs semantic for natural-language queries when vectors are ready, else lexical; lexical may show a labeled semantic fallback only when an identifier-like unscoped query returns zero hits and embeddings are ready.
This returns:
- Pivots: The most relevant symbols with full code bodies
- Neighbors: Connected symbols with signatures only
- File map: Which files contain which symbols
The output is automatically token-budgeted — few results get deep context, many results get broad overview.
Step 1a: Bias with task inputs (optional)
get_context accepts task-shaped inputs that bias pivot selection and neighbor ranking toward what the user is actually working on. Mix and match as relevant:
edited_files=[...]— boost pivots and neighbors in those files. Use when the user has changes in progress and wants context around them.entry_symbols=[...]— explicit symbol entry points the user cares about. Pins those symbols as pivots even if search scoring wouldn't have surfaced them.stack_trace="..."— paste a stack trace;file:linereferences inside get parsed and bias pivot selection toward the frames involved.failing_test="<test file or test symbol>"— boost production symbols linked to that test via the test-linkage graph. Great for "why is this test failing?" orientation.max_hops=2— allow bounded second-hop expansion when first-hop is thin (fewer than 4 code neighbors). Default is 1. Use for sparsely-connected areas where the immediate neighborhood isn't enough.prefer_tests=true— let test-linked symbols compete for neighbor slots alongside production callers. Default isfalse(tests stay out of the neighbor budget). Flip on when the user is writing or debugging tests.
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 · -5 lines 89d34af630bd
- 2mo ago First seen · 154 lines · 49 tokens per session scan A 1c05e9a82b86
explore-area is a skill published in the GitHub repository anortham/julie-plugin (2 stars, last pushed 27d ago), licensed MIT. It adds 49 tokens to every session and 1,602 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to explore-area, differing in 0 lines, and is treated as a copy.
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