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/suboss87/FDEOpsWrote 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/suboss87/fdeops/outcome)<a href="https://agentmods.dev/commands/suboss87/fdeops/outcome"><img src="https://agentmods.dev/badge/commands/suboss87/fdeops/outcome/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/suboss87/fdeops/outcome"><img src="https://agentmods.dev/badge/commands/suboss87/fdeops/outcome.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 | $0.00017 | $0.00270 |
| Opus 5.5 | $0.00007 | $0.00108 |
| Sonnet 5.5 | $0.00003 | $0.00054 |
| Haiku 4.5 | $0.00002 | $0.00027 |
Grade A, and why
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 1mo 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
Load @fde (skills/fde/SKILL.md) and follow its Entry (every session) once. Stage: outcome.
If fde resume shows NO ENGAGEMENT: ask "What should we call this client?" once, then you run fde resume --init. Never tell the human to type the CLI.
Say: "A number nobody signed is claimed, not delivered."
Run fde status (fallback: npx --yes fdeops status). Read the ledger out loud in order: promised → measured → accepted.
Call out gaps: promised but not measured, measured but not accepted, accepted without a named signer. Do not smooth over missing acceptance.
Read references/readout.md and follow it for how to present the ledger and what to offer next.
Do not invent metrics or sign-off. Numbers without a source in .fde/ stay unknown - ask: <question>.
Done when: the human hears the three-beat ledger and agrees what is actually delivered vs still claimed.
Not for a one-line typo in an unbound file. Bound client work, a POC, eval, or go-live stays on @fde.
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.
- 1mo ago Changed 94bd98b256b9
- 1mo ago Changed d88837f09b67
- 1mo ago Changed · +7 tokens per session 3df685886b9d
- 2mo ago First seen · 22 lines · 10 tokens per session scan A 84add7c7c375
outcome is a command published in the GitHub repository suboss87/FDEOps (946 stars, last pushed 10d ago), licensed MIT. It adds 17 tokens to every session and 270 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 2026-08-30.
Other commands, from other repositories
resolve-review
Resolve reviewer feedback - from GitHub PRs, chat, or any reviewer.
implement.body
Every subagent invocation uses the delegation tool with the appropriate subagenttype (the implementation subagent, the tester subagent, or any specialized subagent the project ships). That tool is named Agent, in an interactive session and in the headless runtime alike. Do not look for a Task tool in your toolbox…
agent-build-feature
A strict brief that makes a coding agent implement a feature end to end, matching the codebase and verifying it works.
estimate-work
Estimate a task or project honestly, by decomposing it, surfacing unknowns, and giving a range not a false point.
bug-report-triage
Turn a vague bug report into a structured, actionable ticket with severity and next steps.
decline-politely
Say no clearly and kindly, to a request, invitation, or offer, without burning the relationship or over-explaining.