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/dork-labs/dorkos/feedbackgit clone --depth 1 https://github.com/dork-labs/dorkosWrote 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/dork-labs/dorkos/feedback)<a href="https://agentmods.dev/commands/dork-labs/dorkos/feedback"><img src="https://agentmods.dev/badge/commands/dork-labs/dorkos/feedback.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 | $0.00008 | $0.01031 |
| Opus 5 | $0.00004 | $0.00515 |
| Sonnet 5 | $0.00002 | $0.00206 |
| Haiku 4.5 | $0.00001 | $0.00103 |
Grade A, and why
feedback 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 — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Process Post-Implementation Feedback
Process ONE specific piece of feedback from testing/usage of an implemented spec: explore the affected code, optionally research approaches, gather decisions, and record the outcome in the spec's feedback log.
Phase 1: Validation & Setup
Extract the slug from the spec path (specs/<slug>/02-specification.md → <slug>).
Verify the implementation exists: specs/<slug>/04-implementation.md must be present. If missing, stop with "Run /flow:execute first" (requires the flow plugin, dork-labs/marketplace, loaded via --plugin-dir). If specs/<slug>/03-tasks.json shows incomplete tasks, mention it as a warning — not a blocker.
Phase 2: Feedback Collection
If the user hasn't already provided the feedback, ask for ONE specific piece of feedback from testing (what's wrong or could be improved, with context/repro; one issue per session).
Categorize it: Bug/Error (fail, crash, broken), Performance (slow, timeout), UX/UI (confusing, unclear), Security (auth, permission), or General. The category steers where the exploration looks.
Phase 3: Discovery (background agents)
Always dispatch an Explore agent in the background to investigate the affected code. Its brief: read specs/<slug>/02-specification.md for component names and file paths; investigate the code areas implicated by the feedback type; and report affected components (file paths with how each relates), blast radius (direct changes / indirect impact / tests affected), immediate concerns, and recommended changes per file.
If the issue is complex enough that best-practice research would help (offer the choice for non-obvious issues), also dispatch a research-expert agent in parallel: identify the core technical challenge, compare 2-3 solution approaches with pros/cons, and report a recommended approach plus pitfalls to avoid.
Background agents notify on completion — no polling needed. Continue when their findings are in.
Phase 4: Interactive Decisions
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 · 102 lines · 8 tokens per session scan A fba215b8cf63
feedback is a command published in the GitHub repository dork-labs/dorkos (9 stars, last pushed today), licensed MIT. It adds 8 tokens to every session and 1,031 once invoked, about $0.0000 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 2026-08-31.
Other commands, from other repositories
OPSX: Explore
Enter explore mode - think through ideas, investigate problems, clarify requirements.
OPSX: Apply
Implement tasks from an OpenSpec change (Experimental).
OPSX: Archive
Archive a completed change in the experimental workflow.
OPSX: Propose
Propose a new change - create it and generate all artifacts in one step.
OPSX: Explore
Enter explore mode - think through ideas, investigate problems, clarify requirements.
OPSX: Apply
Implement tasks from an OpenSpec change (Experimental).