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.
git clone --depth 1 https://github.com/ActiveCampaign/activecampaign-pluginWrote 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/commands/activecampaign/activecampaign-plugin/deal-pipeline-review)<a href="https://agentmods.dev/commands/activecampaign/activecampaign-plugin/deal-pipeline-review"><img src="https://agentmods.dev/badge/commands/activecampaign/activecampaign-plugin/deal-pipeline-review/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/commands/activecampaign/activecampaign-plugin/deal-pipeline-review"><img src="https://agentmods.dev/badge/commands/activecampaign/activecampaign-plugin/deal-pipeline-review.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 | $0.00020 | $0.00869 |
| Opus 5 | $0.00010 | $0.00434 |
| Sonnet 5 | $0.00004 | $0.00174 |
| Haiku 4.5 | $0.00002 | $0.00087 |
Grade A, and why
deal-pipeline-review 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 10d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/deal-pipeline-review
Analyze deal pipeline health, velocity, and conversion across stages.
Instructions
When the user runs /deal-pipeline-review, produce a comprehensive analysis of their sales pipeline.
Server rule: The MCP server will not compute win rate, average deal value, total stage value, conversion rate, or time-in-stage, and you must not page the whole deal set to derive them. Show the deals and the counts each query returns, sorted by a supported field (e.g. value). Frame bottlenecks and risk qualitatively from the records you can see. For true pipeline aggregates, point the user to AC's native deal reporting.
Steps
-
Get pipeline structure: Use
list_deal_pipelinesto get pipelines, thenlist_deal_stagesto read each pipeline's stage flow. -
Get deal records by status: Use
list_dealsfiltered by status — open, won, lost — and sorted by value where useful. Report the count each query returns and show the deals. (One call per status per turn; follownext_pageonly to show more deals.) -
Read deals per stage: Show how many deals each query surfaces in each stage and list them. Do not sum stage values into a total or compute a stage-to-stage conversion rate.
-
Deal activity: Use
list_deal_activitieson a few notable deals to describe recent movement qualitatively. -
Present the review in this format:
## Deal Pipeline Review
### Pipeline: [Pipeline Name]
#### Snapshot (counts as returned per status query)
- **Open deals**: [N]
- **Won (in the window queried)**: [N]
- **Lost (in the window queried)**: [N]
> Win rate and average deal value aren't computed here — see AC's native deal reporting.
#### Stage Breakdown
| Stage | Deals (as returned) | Notable deals |
|-------|---------------------|---------------|
| ... | ... | ... |
(Counts and deals as returned — not summed values or conversion rates.)
#### Pipeline Flow
[Stage 1] → [Stage 2] → [Stage 3] → [Won]
[N] deals [N] deals [N] deals [N] deals
(Deal counts per stage as returned. No value totals.)
#### Top Deals (sorted by value, as returned)
1. **[Deal Title]** — $[Value] — Stage: [Stage] — Owner: [Owner]
2. **[Deal Title]** — $[Value] — Stage: [Stage] — Owner: [Owner]
3. **[Deal Title]** — $[Value] — Stage: [Stage] — Owner: [Owner]
#### Observations (qualitative)
- **Possible bottleneck**: [stage with conspicuously many open deals, from the counts]
- **Risk**: [specific deals that appear idle or long-stuck, by name]
#### Recommendations
1. [Highest priority action]
2. [Second priority]
3. [Third priority]
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.
- 10d ago First seen · 75 lines · 20 tokens per session scan A fbbdd7e5f7e4
deal-pipeline-review is a command published in the GitHub repository ActiveCampaign/activecampaign-plugin (0 stars, last pushed 9d ago), licensed MIT. It adds 20 tokens to every session and 869 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
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.
implement
Execute the implementation plan by processing and executing all tasks defined in tasks.md.