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 cynco-labs/ai-accounting-skills --skill resume-engagementgit clone --depth 1 https://github.com/cynco-labs/ai-accounting-skillsWrote 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/cynco-labs/ai-accounting-skills/resume-engagement)<a href="https://agentmods.dev/skills/cynco-labs/ai-accounting-skills/resume-engagement"><img src="https://agentmods.dev/badge/skills/cynco-labs/ai-accounting-skills/resume-engagement/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/cynco-labs/ai-accounting-skills/resume-engagement"><img src="https://agentmods.dev/badge/skills/cynco-labs/ai-accounting-skills/resume-engagement.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 | $0.00025 | $0.00430 |
| Opus 5.5 | $0.00010 | $0.00172 |
| Sonnet 5.5 | $0.00005 | $0.00086 |
| Haiku 4.5 | $0.00003 | $0.00043 |
Grade A, and why
resume-engagement 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 2mo 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
/resume-engagement
Purpose
Make multi-session work safe. Disk is truth.
Workflow
- Find
engagement_state.json:
- cwd, or
- cwd/clients/*/engagement_state.json, or
- path user provides, or
- fixtures path if testing
- Load state +
shared/agent-runtime.md+shared/operator-lens.md+references/stage_artifacts.md - If
operatormissing → resolve once and write it (do not re-ask if inferable) - Verify artifacts listed in
state.artifactsstill exist - Run
python3 scripts/validate_engagement_artifacts.py <client_dir>if workpapers present - Print status board:
## Resume — [legal_name] · [operator] · [engagement_type] · period [fy / on-disk]
- Stage: [current_stage] ([status])
- Completed: [stages_completed]
- Blockers: [blockers or none]
- Open queries: [n]
- Next: [concrete next skill/action]
- If
status == blocked→ work the blocker first - If
status == waiting_on_userandopen_queriesnon-empty → re-issue unanswered asks via structured user-question tool (shared/user-questions.md) — do not only re-printqueries.md - Else continue from
current_stageby loading that stage’s SKILL.md - Do not restart the pipeline from setup unless user says so
If no state file
Say so clearly. Offer:
engagement-setupfor a new clientfull-engagement-pipelineif they dumped files
Completion
Done when: state loaded, one-line status shown, next stage skill identified (or blockers listed).
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.
- 2mo ago First seen · 54 lines · 25 tokens per session scan A abc41ccd9fab
resume-engagement is a skill published in the GitHub repository cynco-labs/ai-accounting-skills (4 stars, last pushed 3mo ago), licensed MIT. It adds 25 tokens to every session and 430 once invoked, about $0.0001 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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