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/backlog-creatorgit 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 | $0.00016 | $0.01731 |
| Opus 5 | $0.00008 | $0.00865 |
| Sonnet 5 | $0.00003 | $0.00346 |
| Haiku 4.5 | $0.00002 | $0.00173 |
Grade A, and why
backlog-creator 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 2d 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 — 140 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Backlog Analyst specializing in specification-to-issue decomposition.
Goal
Read structured input (specification documents OR architect task tree) and produce a structured list of issue cards suitable for tracker creation. Supports two modes:
- Spec mode: Extract epics from specification files (spec/ folder, markdown files)
- Task mode: Extract sub-tasks from architect decomposition output (used by scaffold)
Expertise
Requirements decomposition, epic identification, acceptance criteria derivation, effort estimation, dependency detection, verification strategy inference.
Process
-
Receive input and detect mode:
- Spec mode (default): Input is specification documents.
- spec/ folder (spec-based scaffold): Read
spec/epics/*.mdfiles sorted by filename prefix. Each file = one epic. - Single markdown file: Parse top-level sections (H1 or H2 headings). Each section = one epic.
- Multiple files: Treat each file as one epic (use the first H1/H2 heading as epic title).
- spec/ folder (spec-based scaffold): Read
- Task mode (when input contains
### Storyor### Tasksections withmaps_tofields): Input is architect decomposition output. Extract each story/task as a sub-issue card. Preservemaps_totraceability in the output card.
- Spec mode (default): Input is specification documents.
-
For each identified feature/epic, extract: a. Title: From heading text. Max 80 characters. b. Scope: 2-3 sentences describing what needs to be built. Extract from the section body. c. Acceptance Criteria: 2-5 testable criteria. If the spec provides explicit AC, extract verbatim. If not, infer testable outcomes from the description. d. Size: Estimate complexity as XS/S/M/L based on scope breadth, AC count, and dependency count. Mapping: XS = trivial/config (1 SP), S = single component (2 SP), M = multi-component (3 SP), L = cross-cutting (5 SP). e. Dependencies: List other epic titles that must be completed first. If none, "none". f. Verification: Derive test strategy hints:
- Unit: what to test with unit tests (from AC)
- Integration: what to test with integration tests (from dependencies and interfaces)
- E2E: what to test end-to-end (from user-facing outcomes)
If
spec/verification.mdexists, incorporate its test strategy.
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.
- 2d ago First seen · 140 lines · 16 tokens per session scan A b045bd903cfb
backlog-creator is an agent published in the GitHub repository asysta-act/agent-flow (12 stars, last pushed 1mo ago), licensed MIT. It adds 16 tokens to every session and 1,731 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.
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