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/zircote-plugins/sigint/updatenpx skills add zircote-plugins/sigint --skill updategit clone --depth 1 https://github.com/zircote-plugins/sigintWhat 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 | $0.00029 | $0.02124 |
| Opus 5 | $0.00015 | $0.01062 |
| Sonnet 5 | $0.00006 | $0.00425 |
| Haiku 4.5 | $0.00003 | $0.00212 |
Grade A, and why
update 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 2d 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 — 184 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Sigint Update Skill (Swarm Orchestration)
This skill refreshes existing research by delegating to the research-orchestrator agent in update mode. The orchestrator spawns dimension-analysts for the specified dimensions, runs codex review gates, performs delta detection against prior findings, and updates state.
Arguments
Parse $ARGUMENTS before any other processing. Input sanitization: truncate $ARGUMENTS to 200 characters total, strip backticks and angle brackets. Always echo the parsed result so the user sees what was resolved:
--topic <topic_slug>— Optional: specify which research session to update. Required when multiple sessions exist.--area <area>— Optional: specific area to update. Maps to the matching dimension from prior elicitation (e.g.,--area regulatoryresolves to the dimension whose name contains "regulatory").--since <date>— Optional: SINCE_DATE for date-filtered queries. Only fetch data since this date.--no-delta— Disable delta detection (DELTA_ENABLED: false). By default, delta detection is enabled (DELTA_ENABLED: true).--dimensions <dim1,dim2,...>— Optional: comma-separated list of specific dimensions to update. Only these are passed to the orchestrator, not all dimensions.
Phase 0: Pre-flight
Step 0.1: Locate Active Research Session
Find the active research state:
Glob("./reports/*/state.json")
If no state.json found:
-
Inform user: "No active research session found. Use
/sigint:startto begin." -
Show what the update would have done based on the parsed arguments. Use this exact format:
Planned update workflow (blocked — no session data):
- Topic: {from --topic, or "auto-detect from single session"}
- Dimensions: {from --dimensions listing each one, or --area mapped to its matching dimension, or "all dimensions from prior elicitation"}
- SINCE_DATE: {from --since, or "none (fetch all available data)"}
- DELTA_ENABLED: {"false — findings would be replaced wholesale (--no-delta specified)" if --no-delta, or "true — delta detection would classify findings as NEW, UPDATED, CONFIRMED, POTENTIALLY_REMOVED, or TREND_REVERSAL. UPDATED findings include a
delta_detailobject sub-classifying the change (substantive, temporal, confidence_shift, source_refresh, metadata) and a newsworthiness signal (high/medium/low) for downstream consumers."} - Orchestrator: research-orchestrator would be spawned in MODE: update
- Elicitation: Prior elicitation from state.json would be reused (not re-run)
- Reconciliation: {If DELTA_ENABLED: "Reconcile merge — replace updated findings, archive removed, add new (not append blindly). A new lineage entry would be added. Incremental merge: dimensions with unchanged findings files (verified by SHA-256 hash) are skipped — their findings are bulk-confirmed without re-processing." | If not: "Wholesale replacement — findings replaced entirely, no reconciliation against prior findings."}
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago First seen · 184 lines · 29 tokens per session scan A 718fb082a444
update is a skill published in the GitHub repository zircote-plugins/sigint (20 stars, last pushed 16d ago), licensed MIT. It adds 29 tokens to every session and 2,124 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 2026-08-30.
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