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 skills/ffroliva/gflow-cli/issue-assessmentnpx skills add ffroliva/gflow-cli --skill issue-assessmentgit clone --depth 1 https://github.com/ffroliva/gflow-cliWhat 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 | $0.00090 | $0.01723 |
| Opus 5 | $0.00045 | $0.00861 |
| Sonnet 5 | $0.00018 | $0.00345 |
| Haiku 4.5 | $0.00009 | $0.00172 |
Grade A, and why
issue-assessment 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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
issue-assessment — triage a gflow-cli issue honestly
Read-only conductor. Verify the reporter's claim against the code, tests, docs,
KNOWN_ISSUES.md, and auto-memory; classify it; judge whether it can be
verified end-to-end in the current environment; and draft a reply. The output
is a standard artifact a human or the issue-resolve skill can act on.
Core principle: never assert more than the evidence supports. A claim is
CONFIRMED only with line-level code evidence or a reproduction; a fix is
"verified" only after running it on the affected surface. Honest
"can't verify here" beats a false green check — a bounced fix costs more trust
than an accurate "not yet."
When to invoke
- A new or updated GitHub issue needs a verdict before anyone spends effort.
- An autonomous run (hermes-ops) reacts to an issue labelled for triage.
- You're about to "just fix" a reported bug — assess first; the scope decision
(reply-only vs hand to
issue-resolve) depends on this.
Skip for: issues that are obviously feature requests routed elsewhere, or already-triaged issues entering implementation.
Invocation
/gflow:issue-assessment <issue number or URL>
This repo's skills/*/SKILL.md are plain Markdown — invoke by reading the
file (via the .claude/commands/gflow/* wrapper), never Skill(skill=...).
Protocol
1. Ingest
gh issue view <N> --json title,body,comments,labels,author,state. Extract: the
claimed symptom, environment (OS, version, install method), exact repro steps,
and any logs/error classes the reporter pasted.
2. Verify (read-only)
Dispatch a search/Explore agent (keep your own context clean) to corroborate or refute the claim against the real tree. Always check, in order:
- the source path(s) the symptom implicates — cite
file_path:line_number; KNOWN_ISSUES.md(is this Open / Mitigated / Resolved already?);- open issues/PRs (
gh pr list,gh issue list) for duplicates or in-flight fixes; - auto-memory for prior context on the surface.
Disprove parts of the reporter's framing where the code says otherwise (e.g.
browser_engine: playwrightis the engine axis, not the channel) — a precise correction is more useful than agreement.
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 · 149 lines · 90 tokens per session scan A 921276f980bb
issue-assessment is a skill published in the GitHub repository ffroliva/gflow-cli (136 stars, last pushed 3d ago), licensed MIT. It adds 90 tokens to every session and 1,723 once invoked, about $0.0005 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.
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