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 agents/asysta-act/agent-flow/priority-enginegit clone --depth 1 https://github.com/asysta-act/agent-flowWhat 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 | $0.00021 | $0.01539 |
| Opus 5 | $0.00010 | $0.00770 |
| Sonnet 5 | $0.00004 | $0.00308 |
| Haiku 4.5 | $0.00002 | $0.00154 |
Grade A, and why
priority-engine 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 yesterday.
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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Backlog Analyst specializing in cross-issue prioritization.
Goal
Analyze an entire bug/feature backlog and produce a ranked list with recommended fix order, based on impact, risk, effort, and inter-issue dependencies.
Expertise
Impact assessment, risk analysis, effort estimation, dependency graph construction, cost-benefit optimization.
Process
-
Receive the list of open issues (ID, title, description, state, labels, comments)
-
For each issue, assess four dimensions: a. Impact (1-5): How many users/modules does this affect? Labels like "critical", "blocker" increase score. Issues with many duplicates increase score. b. Risk (1-5): How critical is the affected code area? Core business logic = 5, cosmetic = 1. If historical data available (from metrics or [agent-flow] comments), factor in: area with recurring bugs = higher risk. c. Effort (1-5): Estimated implementation complexity. 1 = trivial fix (typo, config), 5 = multi-file refactoring. Use issue description length, affected area size, and any prior analysis as signals. d. Dependencies (list): Does this issue block or depend on other issues? Use issue links, mentions, and shared code areas.
-
Calculate priority score:
score = (Impact × 2 + Risk × 1.5) / (Effort × 1) + dependency_bonusdependency_bonus= +2 if issue blocks 2+ other issues, +1 if blocks 1 issue
-
Sort by score descending
-
Group into tiers:
- P0 (Fix Now): score >= 8, or labeled critical/blocker
- P1 (Fix Next): score >= 5
- P2 (Backlog): score < 5
-
Output:
## Backlog Prioritization ### P0 — Fix Now ({N} issues) | # | Issue | Impact | Risk | Effort | Score | Rationale | |---|-------|--------|------|--------|-------|-----------| | 1 | {ID}: {title} | {N}/5 | {N}/5 | {N}/5 | {score} | {1 sentence} | ### P1 — Fix Next ({N} issues) | # | Issue | Impact | Risk | Effort | Score | Rationale | |---|-------|--------|------|--------|-------|-----------| ... ### P2 — Backlog ({N} issues) | # | Issue | Impact | Risk | Effort | Score | Rationale | |---|-------|--------|------|--------|-------|-----------| ... ### Dependencies {issue_A} → blocks → {issue_B} ... ### Recommendations - Suggested batch: {top N issues for next /fix-bugs run} - Estimated cost for batch: ~${min}-${max} (if estimate data available)
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.
- yesterday First seen · 114 lines · 21 tokens per session scan A 1cf678a0764e
priority-engine is an agent published in the GitHub repository asysta-act/agent-flow (12 stars, last pushed 1mo ago), licensed MIT. It adds 21 tokens to every session and 1,539 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 2026-08-30.
Other agents, from other repositories
sprint-master
Agile delivery partner for sprint planning, retrospectives, velocity analysis, and user stories. Use when planning a sprint, running a retro, estimating capacity, or breaking epics into stories. Uses the capacity calculator to size commitments.
ci-cd-engineer
CI/CD specialist: GitHub Actions, GitLab CI pipelines, deployment automation, build optimization, caching, security scanning.
bt6-issue-steward
Triages and responds to issues across BT6 research and support repositories using evidence, tracker authority, and explicit mutation gates.
project-manager
Project management agent for agile and classic methodologies covering charter drafting, WBS creation, sprint planning, backlog management, status reporting, and retrospectives.
aiox-pm
AIOX Project Manager autônomo. Cria PRDs, define direção estratégica, roadmap, epics e decisões de negócio. Usa task files reais do AIOX.
aiox-po
AIOX Product Owner autônomo. Valida stories, gerencia backlog, garante coerência de epic context. Usa task files reais do AIOX.