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 commands/cwensel/arcaneum/searchgit clone --depth 1 https://github.com/cwensel/arcaneumWrote 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/commands/cwensel/arcaneum/search)<a href="https://agentmods.dev/commands/cwensel/arcaneum/search"><img src="https://agentmods.dev/badge/commands/cwensel/arcaneum/search.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 | $0.00003 | $0.00581 |
| Opus 5 | $0.00002 | $0.00291 |
| Sonnet 5 | $0.00001 | $0.00116 |
| Haiku 4.5 | $0.00000 | $0.00058 |
Grade A, and why
search 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.
What it actually says
Search your indexed content using semantic search (most common) or full-text search.
Quick Start - Most Common Usage:
arc search semantic "your query here" --corpus CorpusName
IMPORTANT: The subcommand (semantic or text) comes BEFORE the query.
Subcommands (required):
semantic: Vector-based semantic search (Qdrant)text: Keyword-based full-text search (MeiliSearch)
Examples:
# Semantic search (most common)
/arc:search semantic "identity proofing" --corpus Standards
/arc:search semantic "authentication logic" --corpus MyCode --limit 5
# Multi-corpus search
/arc:search semantic "authentication" --corpus Code --corpus Docs
# Full-text keyword search
/arc:search text "def authenticate" --corpus MyCode
Common Options:
- --corpus: Corpus/collection to search (can specify multiple times)
- --limit: Number of results to return (default: 10)
- --offset: Number of results to skip for pagination (default: 0)
- --filter: Metadata filter (key=value or JSON)
- --json: Output in JSON format
- --verbose: Show detailed information
Semantic Search Options:
- --vector-name: Vector name (auto-detected if not specified)
- --score-threshold: Minimum similarity score
Execution:
arc search $ARGUMENTS
When to Use Each:
Semantic Search (vector-based):
- Finding conceptually similar code/documents
- Cross-language semantic matching
- "What does this" or "How to" questions
- Fuzzy concept matching
Full-Text Search (keyword-based):
- Exact keyword or phrase matching
- Function/variable name search
- Quoted phrase search
- Boolean operators (AND, OR, NOT)
Result Format:
Both commands show:
- Relevance score (similarity for semantic, rank for text)
- Source file path
- Matching content snippet
- Metadata (git info for code, page numbers for PDFs)
Related Commands:
- /arc:corpus create - Create corpus for dual indexing (recommended)
- /arc:corpus sync - Index content to both systems
- /arc:corpus list - List available corpora
- /arc:collection list - See available collections (semantic only)
Implementation:
- RDR-007: Semantic search via Qdrant
- RDR-012: Full-text search via MeiliSearch
- RDR-006: Claude Code integration
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 · 92 lines · 3 tokens per session scan A e133bcead48c
search is a command published in the GitHub repository cwensel/arcaneum (7 stars, last pushed 8d ago), licensed MIT. It adds 3 tokens to every session and 581 once invoked, about $0.0000 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.
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clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.