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 gs-bbluhm/gainsight-mcp-plugins --skill staircase-risk-checkgit clone --depth 1 https://github.com/gs-bbluhm/gainsight-mcp-pluginsWrote 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/gs-bbluhm/gainsight-mcp-plugins/staircase-risk-check)<a href="https://agentmods.dev/skills/gs-bbluhm/gainsight-mcp-plugins/staircase-risk-check"><img src="https://agentmods.dev/badge/skills/gs-bbluhm/gainsight-mcp-plugins/staircase-risk-check/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/gs-bbluhm/gainsight-mcp-plugins/staircase-risk-check"><img src="https://agentmods.dev/badge/skills/gs-bbluhm/gainsight-mcp-plugins/staircase-risk-check.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 | $0.00093 | $0.01235 |
| Opus 5.5 | $0.00037 | $0.00494 |
| Sonnet 5.5 | $0.00019 | $0.00247 |
| Haiku 4.5 | $0.00009 | $0.00123 |
Grade A, and why
staircase-risk-check 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 25d 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 — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Staircase Risk Check
A grounded health read for one account. Not a vibe and not a score: the actual frustration, disengagement, and churn signals in the communications, quoted with their source, balanced against the strengths, with a clear trajectory and the one or two things to do this week.
Foundation references
Read these before composing the query if you have not in this session:
../staircase-mcp-expert/: query mechanics, the Risk Analysis data model, non-determinism handling.../../_shared/staircase-output-best-practices.md: the house style. Note: in Staircase R/Y/G displays, yellow means average/neutral, never "concern".
When to use
Trigger phrases:
- "risk check on [account]"
- "is [account] at risk" / "should I be worried about [account]"
- "health check on [account]"
- "any red flags on [account]"
- "how healthy is [account]"
Optimized for: Cowork (card + sections) and Code (markdown + optional file).
Step 1: Resolve the account
Call staircase_account_lookup(name=<account>) first.
- High-confidence single match: proceed.
- Multiple low-confidence matches: STOP and ask which account. Do not guess.
- No match: say so and ask for an alternate name.
Step 2: Run the risk query
Use the validated Risk Check prompt verbatim via staircase_analyze_account.
staircase_analyze_account(account_id, query="
Assess the health and risk signals for <Account> from the last 90 days of communication. Identify: (1) specific signals of frustration, disengagement, or churn risk with the exact language and source, (2) signals of strength or satisfaction, (3) the sentiment trajectory and since when, (4) stakeholder or responsiveness patterns that change the picture, and (5) a clear risk read with the top 1-2 actions this week. Distinguish evidenced from inferred.")
Non-determinism: re-run the same phrasing once or twice if thin; trust an honest negative as a real signal of low communication, not hidden data.
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.
- 25d ago First seen · 110 lines · 93 tokens per session scan A ed68530d818f
staircase-risk-check is a skill published in the GitHub repository gs-bbluhm/gainsight-mcp-plugins (4 stars, last pushed 20d ago), licensed MIT. It adds 93 tokens to every session and 1,235 once invoked, about $0.0004 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 2026-09-26.
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