Borrowing it
Nothing to install: this file belongs to Federico-Anastasi/DYLA-ai. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/Federico-Anastasi/DYLA-ai/main/.agents/skills/pipeline/SKILL.mdgit clone --depth 1 https://github.com/Federico-Anastasi/DYLA-aiWrote 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/skills/federico-anastasi/dyla-ai/pipeline)<a href="https://agentmods.dev/skills/federico-anastasi/dyla-ai/pipeline"><img src="https://agentmods.dev/badge/skills/federico-anastasi/dyla-ai/pipeline/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/skills/federico-anastasi/dyla-ai/pipeline"><img src="https://agentmods.dev/badge/skills/federico-anastasi/dyla-ai/pipeline.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 | $0.00053 | $0.02109 |
| Opus 5.5 | $0.00021 | $0.00844 |
| Sonnet 5.5 | $0.00011 | $0.00422 |
| Haiku 4.5 | $0.00005 | $0.00211 |
Grade A, and why
pipeline 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 2mo 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 — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/pipeline — The full run
Runs the entire estimation flow in a single session. For individual deliverables, use the modular skills.
UX: chat stays conversational. No deliverable is ever presented as a markdown table in
chat — every phase writes the JSON FIRST (meta.status: "draft"), the user reads it in
the viewer, and then it gets discussed in words, citing elements by id. On confirmation
meta.status becomes "confirmed". When you cite a chapter of the brief, write
[[brief:Chapter title]]: it renders as a clickable reference that opens the document at
that point.
The skills this composes:
/meeting— merges a meeting transcript into the brief/data-model— data model (tables, relations, integrations)/estimate— the work plan in days/dev-tasks— the granular dev task breakdown/mockup— component-based mockup
Each phase below follows the protocol of the corresponding skill. Read that skill's SKILL.md when you need the detail — this file is the running order, not a replacement for them.
THE FLOW
[MEETING, if needed] → INTAKE → Q&A [STOP] → DATA MODEL [STOP] → ESTIMATE [STOP] → DEV TASKS → MOCKUP
Three blocking points: Q&A, data model, estimate. The user confirms before you go on.
PHASE 0 — MEETING (conditional)
Read projects/{project}/.project.json. If source is "discovery" and
projects/{project}/meetings/ holds transcripts not yet merged into brief.json (compare
with changelog[].source), the pipeline starts there: run /meeting first to merge them
and bring the brief to a stable state, then continue from PHASE 1. If the brief is already
current (or the project source is brief), skip this phase.
PHASE 1 — INTAKE
Invoked with a file
/pipeline path/to/brief.md
Read the file. That is your main input.
Invoked with nothing
Look for the brief in the project folder: brief.json (source discovery) or brief.*
as an input document (if it is a PDF or a Word file, read the extracted text under
.extracted/). If there is none, ask.
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.
- 2mo ago First seen · 199 lines · 53 tokens per session scan A f76337c0d79f
pipeline is a skill published in the GitHub repository Federico-Anastasi/DYLA-ai (1 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 2,109 once invoked, about $0.0002 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 2026-08-31.
Other skills, from other repositories
trailhead-view
Skill "trailhead-view" from ToRvaLDz/trailhead, covering load first, in order, routing: verb to engine, render the map: map [map], 🎯 destination and 🗒️ notes.
plan
Use when operating as the Fabrik Plan stage agent. This skill guides the design of an implementation approach, producing a concrete plan with task checklist that the Implement stage will follow.
implement-comment
Use when operating as the Fabrik Implement comment reviewer. This skill guides applying user-requested code changes during implementation, committing and pushing, and updating the task checklist — without signaling stage completion.
fabrik-setup
Bootstrap a project to use Fabrik (the GitHub-Project-driven SDLC pipeline orchestrator that drives Claude Code workers through Specify/Research/Plan/Implement/Review/Validate stages). Use this skill when the user wants to install, set up, initialize, or get started with Fabrik for the first time — especially when…
specify
Use when operating as the Fabrik Specify stage agent. This skill guides the specification and clarification of a feature request, turning a rough backlog issue into a clear, unambiguous spec before technical research begins.
specify-comment
Use when operating as the Fabrik Specify comment reviewer. This skill guides incorporation of user answers into an evolving spec, removing resolved questions and surfacing follow-ups until the spec is complete.