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 ethanaubuchon/dossier-tradecraft --skill dispatch-explorationgit clone --depth 1 https://github.com/ethanaubuchon/dossier-tradecraftWrote 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/ethanaubuchon/dossier-tradecraft/dispatch-exploration)<a href="https://agentmods.dev/skills/ethanaubuchon/dossier-tradecraft/dispatch-exploration"><img src="https://agentmods.dev/badge/skills/ethanaubuchon/dossier-tradecraft/dispatch-exploration/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/ethanaubuchon/dossier-tradecraft/dispatch-exploration"><img src="https://agentmods.dev/badge/skills/ethanaubuchon/dossier-tradecraft/dispatch-exploration.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 | $0.00085 | $0.02594 |
| Opus 5.5 | $0.00034 | $0.01038 |
| Sonnet 5.5 | $0.00017 | $0.00519 |
| Haiku 4.5 | $0.00009 | $0.00259 |
Grade A, and why
dispatch-exploration 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.
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Dispatch Exploration
Send a small batch of research queries to specialist agents in parallel, apply the cross-verify consent gate when a returned finding triggers it, and return a compressed findings list.
Input
A list of query objects:
[
{"question": "what does Ethan want re: relocation healthcare costs?", "target": "vault", "hint": "projects/relocation"},
{"question": "current state of Spain non-lucrative visa for US remote workers", "target": "web"}
]
target—"vault"or"web". Required.hint(vault only) — optional slug-prefix scope to focus the search.
The input shape is stable — callers do not need to opt into the cross-verify gate; it is always on for target: "web" results.
Process
-
Dispatch one agent per query, all in parallel (single message, multiple Agent tool calls):
target: "vault"→vault-researchertarget: "web"→web-researcher
-
Wait for all results.
-
Cross-verify intercept for each
webresult. See Cross-verify orchestration below. This is the only step where this skill may pause for user interaction; vault results are pass-through. -
Build a compressed findings list, one line (or short block) per query:
Vault result:
<query> → <slug> — <relevance> — <excerpt>or
<query> → no matchif the agent returnednone.Web result (default):
<query> → <summary> — <top 1-2 citations> — cohort: <cohort_spread> — flags: <flag list>Pass through
cohort_spreadandflagswhen present. Omit thecohort:/flags:segments when the agent returned no flags and a single-cohort spread (e.g. an evergreen-fact lookup with a clean sample).Web result (pricing mode, single tier):
<query> → new: median $Y, range $A–$B (N reputable sources) — flags: <flags>Web result (pricing mode, tiered after consent):
<query> new: median $Y, range $A–$B (N sources, manufacturer-direct + major-retailer) used: median $Z, range $C–$D (M sources, marketplace-used / refurbished / etc.) flags: <flags>
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 First seen · 186 lines · 85 tokens per session scan A 25f482caf06c
dispatch-exploration is a skill published in the GitHub repository ethanaubuchon/dossier-tradecraft (3 stars, last pushed 8d ago), licensed MIT. It adds 85 tokens to every session and 2,594 once invoked, about $0.0003 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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