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/activecampaign/activecampaign-plugin/automation-auditgit clone --depth 1 https://github.com/ActiveCampaign/activecampaign-pluginWhat 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 | $0.00025 | $0.00799 |
| Opus 5 | $0.00013 | $0.00400 |
| Sonnet 5 | $0.00005 | $0.00160 |
| Haiku 4.5 | $0.00003 | $0.00080 |
Grade A, and why
automation-audit 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 3d 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 — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/automation-audit
Review automation performance and identify automations that need attention.
Instructions
When the user runs /automation-audit, analyze all active automations and surface issues, opportunities, and recommendations.
Server rule: The MCP server does not compute aggregates, so a true account-wide "completion rate" or "average duration" is not available.
list_automationsreturns each automation's name, status, and the contact counts the API exposes on the record itself (e.g. entered / completed counts). Report those per-automation numbers as returned. Do not page throughlist_contact_automationsfor every contact to compute a rate yourself — that violates the server's rules and is what AC's native automation reporting is for. Frame "needs attention" qualitatively from the per-record numbers, not from a threshold you calculated across the dataset.
Steps
-
Get all automations: Use
list_automationsto fetch automations and their status (active/disabled) plus whatever entered/completed counts the records carry. (One call per turn; follownext_pageonly to show more automations.) -
Read per-automation signals from the records themselves: For each automation, use the counts already present on the
list_automationsrecord — entered count, completed count, status. If the user wants detail on one specific automation, you may uselist_contact_automationsfiltered to that automation to show individual run statuses — but describe them qualitatively, don't compute a fleet-wide percentage. -
Flag qualitatively (based only on the returned per-record numbers):
- Automations where the record shows many entered but few completed — note as a possible drop-off to investigate in native reporting
- Stale — active but the record shows little/no recent entry
- No goals set — automations without a measurable outcome
- Possible overlap — multiple automations that appear to target the same audience
-
Present the audit in this format:
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.
- 3d ago First seen · 67 lines · 25 tokens per session scan A 55ccad533f72
automation-audit is a command published in the GitHub repository ActiveCampaign/activecampaign-plugin (0 stars, last pushed 2d ago), licensed MIT. It adds 25 tokens to every session and 799 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.
Other commands, from other repositories
README
Git workflow and quality assurance commands for the claude-skills repository.
obsidian-recap
Summarize a time period from the vault - today, week, or month.
design-review
Workflow recipe — review a design end-to-end, ending in measured numbers rather than adjectives, by chaining 4 skills.
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
autobot-result
Print the most recent result.md for an autobot session, so the user can see how a bot is doing without attaching to its tmux session.
engage.actions
Execute Phase 7 - Actions on Objectives and Goal Achievement.