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/mistakeknot/interdeep/deep-researchnpx skills add mistakeknot/interdeep --skill deep-researchgit clone --depth 1 https://github.com/mistakeknot/interdeepWhat 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 | $0.00019 | $0.01232 |
| Opus 5 | $0.00010 | $0.00616 |
| Sonnet 5 | $0.00004 | $0.00246 |
| Haiku 4.5 | $0.00002 | $0.00123 |
Grade A, and why
deep-research 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.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/interdeep:deep-research
Orchestrate a deep research session: decompose a query, search multiple sources, extract and evaluate content, synthesize findings, and persist the result.
Protocol
Execute these five phases in order. Adapt depth based on the mode (see Depth Modes below).
Phase 1: Orient
- Use the research-planner agent to decompose the query into sub-queries with source routing.
- Review the planner output:
query_type,sub_queries(each withquery,sources,priority),depth_recommendation,rationale. - If the user did not specify a depth mode, use the planner's
depth_recommendation.
Phase 2: Search
For each sub-query, dispatch searches to the routed sources:
- Web search — call
interject_search(interject plugin) orweb_search_exa(interflux/exa plugin):mcp tool: interject_search args: { "query": "<sub_query>", "source": "exa", "max_results": 10 } - Academic — call
interject_searchwith"source": "arxiv". - Knowledge base — call
interknow_qmd__searchorinterknow_qmd__vector_search(interknow plugin) for local knowledge. - Cached results — check
intercacheif available to avoid redundant fetches.
Collect URLs and snippets from all search results.
Phase 3: Extract
For each URL returned in Phase 2:
- Call
extract_content(interdeep MCP tool) for single URLs:mcp tool: extract_content args: { "url": "<url>", "include_metadata": true } - For batches (5+ URLs), use
extract_batch:mcp tool: extract_batch args: { "urls": ["<url1>", "<url2>", ...], "max_concurrent": 5 } - Use the source-evaluator agent on each extraction result to score relevance and credibility.
- Filter to sources where
include_in_reportis true.
Phase 4: Synthesize
- If interlens is available, call
detect_thinking_gapsto identify blind spots:mcp tool: detect_thinking_gaps args: { "context": "<research summary so far>" } - If gaps are found and depth mode is
deep, run additional searches targeting the gaps. - Pass evaluated findings to the report-compiler agent.
- Alternatively, call
compile_report(interdeep MCP tool) for a structured markdown report:mcp tool: compile_report args: { "title": "<report title>", "query": "<original query>", "findings": [...], "sources": [...] } - If intersynth is available, use it for additional synthesis passes.
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 · 129 lines · 19 tokens per session scan A 9f1a8b8a70d7
deep-research is a skill published in the GitHub repository mistakeknot/interdeep (0 stars, last pushed 1mo ago), licensed MIT. It adds 19 tokens to every session and 1,232 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.
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