Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add sigistry/marketplace/plugin install recordsWrote 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/sigistry/marketplace/explain-outcome)<a href="https://agentmods.dev/commands/sigistry/marketplace/explain-outcome"><img src="https://agentmods.dev/badge/commands/sigistry/marketplace/explain-outcome.svg" alt="Measured on agentmods" 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 | $0.00015 | $0.00205 |
| Opus 5 | $0.00008 | $0.00102 |
| Sonnet 5 | $0.00003 | $0.00041 |
| Haiku 4.5 | $0.00002 | $0.00020 |
Grade A, and why
explain-outcome 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 4d 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
Explain FHIR OperationOutcome
Use /records:fhir-validation and read skills/fhir-validation/references/operationoutcome-map.md.
Input: $ARGUMENTS, pasted JSON, or a file path.
When a file path is available, prefer:
node "${CLAUDE_PLUGIN_ROOT}/skills/fhir-validation/scripts/explain-operationoutcome.mjs" "$ARGUMENTS"
Explain issues by severity and expression/path. For each issue:
- Translate the validator message into plain language.
- Classify the likely next step as safe mechanical fix, domain input, or setup/package repair.
- Note whether the issue may come from missing IG packages, profiles, terminology, or stale generated artifacts.
- Avoid printing complete Patient resources or unnecessary identifiers.
Do not claim a validation run happened unless one was actually executed.
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.
- 4d ago First seen · 26 lines · 15 tokens per session scan A e6db214af0ef
explain-outcome is a command published in the GitHub repository sigistry/marketplace (3 stars, last pushed 4d ago), licensed MIT. It adds 15 tokens to every session and 205 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 2026-09-03.
Other commands, from other repositories
octo-loop
Your first output line MUST be: 🐙 Octopus Loop Mode.
octo-debug
Debug a symptom through reproducible, bounded evidence.
five-whys
Use the "Five Whys" root cause analysis technique to deeply understand problems.
debug
Structured debugging with parallel investigation agents.
bugfix
TDD-driven bugfix workflow: tester writes failing test (RED) → developer fixes (GREEN) → developer refactors (REFACTOR) → reviewer validates. Accepts issue number, description, or both. Auto-creates PR unless --no-pr flag is passed.
fec-tdd
Use front-end TDD workflow to implement functions, fix bugs, or refactor logic: first write failing tests, then implement minimal code, and then refactor.