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Agent skill

Safe AI Dlc

by bybren-llc in bybren-llc/safe-agentic-workflow

Plan and run programs using the SAFe x AI-DLC fusion. An agent skill from bybren-llc/safe-agentic-workflow.

MITAuto-check passedAgent Workflows

Install Safe AI Dlc

skills CLI
$ npx skills add bybren-llc/safe-agentic-workflow --skill safe-ai-dlc -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install bybren-llc/safe-agentic-workflow safe-ai-dlc --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/bybren-llc/safe-agentic-workflow.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.agents/skills/safe-ai-dlc .claude/skills/safe-ai-dlc && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
safe-ai-dlc
GitHub stars
423
Token cost
~1.9k tokens
SKILL.md length
708 words
Files
4 (incl. scripts, references, assets)
Skills in repo
42
Repo updated
First seen
Licence
MIT

At a glance

Plan and run programs using the SAFe x AI-DLC fusion. An agent skill from bybren-llc/safe-agentic-workflow.

  • Works in 6 steps: Initiative = the program. One per program. → Projects = Units of Work. One coherent… → Milestones = the three AI-DLC phases… → …
  • Turning an audit
  • SKILL.md covers Purpose, When This Skill Applies, The Fusion Model and How to Structure the Program, plus 7 more sections
  • Initiative into tracker structure (initiative

What it does

Safe AI Dlc is an agent skill from bybren-llc/safe-agentic-workflow. Plan and run programs using the SAFe x AI-DLC fusion. Use when turning an audit, epic, or initiative into tracker structure (initiative, projects, milestones, issues, sub-issues), organizing work as Units of Work and Bolts, wiring a dependency DAG, or running a Bolt swarm with a human-in-the-loop gate. Applies when work spans multiple issues and needs cadence.

Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts, reference files and assets.

It sits in Agent Workflows, covering Project management and Human-in-the-loop approvals. It works with xAI Grok. The repository describes itself as: SAW — SAFe Agentic Workflow AI Agent Harness for Multi-Agent Team Workflows Built on SAFe methodology (Scaled Agile Framework), adapted for AI agent teams (Now With AI-DLC!)… The licence is MIT.

When your agent uses it

  • Turning an audit
  • Initiative into tracker structure (initiative
  • Organizing work as Units of Work and Bolts
  • Wiring a dependency DAG

Example prompts

  • “/safe-ai-dlc”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Initiative = the program. One per program.
  2. Projects = Units of Work. One coherent outcome each.
  3. Milestones = the three AI-DLC phases (Inception, Construction, Operations). Create all three
  4. Issues = Stories. Each carries the issue template below. Label with bolt:N and agent:*
  5. Sub-issues = Mob Elaboration tasks. Create during Inception, not before.
  6. Dependencies = blocks / blockedBy edges forming the dependency DAG.

What it can do on your machine

Read from SKILL.md and the folder at commit 26ca58b. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • aws.amazon.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Safe AI Dlc loads about 1.9k tokens when it runs. Until then it costs about 94 tokens; SKILL.md has 708 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~94
When it runs · the whole SKILL.md, loaded when a task matches
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from bybren-llc/safe-agentic-workflow at commit 26ca58b, republished under its MIT licence (© bybren-llc). 708 words, ~1,852 tokens.

Download SKILL.mdSave it as .claude/skills/safe-ai-dlc/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
safe-ai-dlc
description
Plan and run programs using the SAFe x AI-DLC fusion. Use when turning an audit, epic, or initiative into tracker structure (initiative, projects, milestones, issues, sub-issues), organizing work as Units of Work and Bolts, wiring a dependency DAG, or running a Bolt swarm with a human-in-the-loop gate. Applies when work spans multiple issues and needs cadence.

SAFe x AI-DLC Skill

TEMPLATE: This skill uses {{PLACEHOLDER}} tokens. Replace with your project values before use.

Purpose

Encode the SAFe x AI-DLC fusion so agents structure multi-issue programs consistently: SAFe supplies the hierarchy and guardrails, AI-DLC supplies the cadence and the human checkpoint. Inside a program that adopts this fusion, sprints give way to Bolts, because agent teams elaborate, build, and verify in hours rather than weeks. Adopting the fusion is a per-program choice; the standard sprint path stays valid, and single isolated tickets route to safe-workflow instead.

When This Skill Applies

  • Turning an audit, epic, or initiative into an executable program
  • Structuring work in the tracker as initiative, projects, milestones, issues, and sub-issues
  • Breaking an initiative into Units of Work and sequencing them into Bolts
  • Wiring dependencies so gates land before the fixes they verify
  • Running a Bolt: elaborate, validate with the human, construct, verify gates are real, evidence, merge

Do NOT use it for a single isolated ticket with no program context — use safe-workflow for that.

The Fusion Model

SAFe gives hierarchy, WSJF, roles, DoD, and dependencies. AI-DLC gives cadence (Bolts) and the human-in-the-loop.

SAFeAI-DLCTracker object
Portfolio EpicThe ProgramInitiative
Epic/value streamProgram streamSub-initiative, or project priority
FeatureUnit of WorkProject
PI incrementBoltbolt:N label + target date
Phase gateInception / Construction / OperationsProject Milestone (3 per project)
Story/EnablerStoryIssue
TaskMob taskSub-issue
WSJF/Role/DoDprioritization / mob role / gatedescription + agent:* labels + AC/DoD

The loop: AI plans, AI asks clarifying questions, the HUMAN validates business context, then AI executes. Never skip the human validation step.

How to Structure the Program

Build top-down:

  1. Initiative = the program. One per program.
  2. Projects = Units of Work. One coherent outcome each.
  3. Milestones = the three AI-DLC phases (Inception, Construction, Operations). Create all three per project.
  4. Issues = Stories. Each carries the issue template below. Label with bolt:N and agent:* (lead role).
  5. Sub-issues = Mob Elaboration tasks. Create during Inception, not before.
  6. Dependencies = blocks / blockedBy edges forming the dependency DAG.

Program streams map to sub-initiatives where the tracker plan supports them; where it does not, encode the stream as project priority instead (highest-risk stream = Urgent/High).

Use linear-sop for tracker operations, label prerequisites, and evidence templates.

Issue Template

Every issue description block contains:

text
Header:      <ID> — <title>  [{{TICKET_PREFIX}}-XXX]
WSJF:        <score>   MoSCoW: <Must|Should|Could|Won't>
Finding:     <source refs, e.g. audit finding IDs>
Phase:       <Inception | Construction | Operations>
Bolt:        <bolt:N>
Role:        <agent:* lead>
AC:          - acceptance criterion (testable)
DoD:         - merged to {{MAIN_BRANCH}}; relevant gate REAL and green; evidence in tracker;
               no silent suppression
Deps:        blocks: [...]   blockedBy: [...]
Sub-issues:  (Mob Elaboration tasks, added during Inception)
Show full SKILL.md (330 more words)Show less

Dependency-Wiring Rules

Wire blocks / blockedBy so the enforcement lands before the thing it enforces:

  • Fix the gate before the fix it verifies. Harden CI or un-mask a check before landing the fix that check is supposed to catch.
  • Rotate before scrub. Rotate a leaked credential before scrubbing it from history.
  • Capture before alert. Error capture or health check blocks the alerter and the poller built on top of it.
  • Upgrades before re-baseline. Framework and SDK upgrades block audit re-baselining, which blocks the scheduled recurring audit.

Dependency chains are usually rooted at CI hardening — one keystone issue tends to unblock a whole stream. Identify it and sequence its Bolt first.

Running a Bolt

  1. Open and elaborate every issue in the Bolt (Mob Elaboration: sub-issues, unknowns, questions).
  2. Validate with the human on all business, security, and policy decisions before Construction.
  3. Construct in dependency order on {{TICKET_PREFIX}}- branches with SAFe commits, rebase-first.
  4. Verify gates are real — a green check that still masks a failure is not an exit.
  5. Post evidence to the tracker (dev/staging/done) per linear-sop.
  6. Merge — RTE prepares the PR; the human (HITL) merges. Exit = merged + real gates green + evidence posted.

Human-Gate Checklist

Route to the human, with options and a recommendation, whenever a decision is:

  • A secret or credential action (what to rotate, when, blast radius)
  • A security policy: CSP allow-list, auth behavior, headers
  • A CI or branch-protection decision: which checks become required
  • A severity or risk policy: dependency-audit thresholds, fix-vs-suppress budget
  • An SOP exception (e.g. a migration deviating from the documented process)
  • Signing the Definition of Done

If a decision changes business, security, or risk posture, it is the human's — surface, recommend, stop.

Anti-Patterns (Do NOT use)

text
Forcing an ambiguous epic into one Bolt    (run a spike instead — elaboration is the hard part)
Creating sub-issues before Inception       (Mob Elaboration produces them, not the other way round)
Bolts as calendar sprints                  (a Bolt exits on evidence, not on a date)
Skipping human validation to move faster   (the loop is the method; without it this is just SAFe)
Treating a green check as an exit          (verify the gate enforces, not that it merely passed)

Reference

Routes To

  • linear-sop — tracker operations, program structure, evidence templates
  • safe-workflow — branch, commit, and PR conventions; HITL merge
  • orchestration-patterns — multi-agent swarm coordination for a Bolt
  • pattern-discovery — find existing code and doc patterns before constructing

© bybren-llc, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references, assets) in .agents/skills/safe-ai-dlc of bybren-llc/safe-agentic-workflow.

  • SKILL.md
  • assets/.gitkeep
  • references/.gitkeep
  • scripts/.gitkeep

Open the folder on GitHubat commit 26ca58b

Compare with similar skills

Safe AI Dlc next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Safe AI Dlc compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Safe AI Dlc this skillbybren-llc/safe-agentic-workflow423—~1.9kAutomated safety check: PassMIT
Coherence AuditorGoogleChrome/modern-web-guidance-src1.1k—~864Automated safety check: PassApache-2.0
Mps Project ManagementJetBrains/MPS1.7k—~2.2kAutomated safety check: PassApache-2.0
Init My ProjectMCSLTeam/MCServerLauncher-Future121—~2.1kAutomated safety check: PassGPL-3.0
Gh Issuesserejaris/personal-corp-os229—~1.8kAutomated safety check: PassMIT
Requirement Ledger Workflowadand-91/gpt-6-astra-skill125—~6.3kAutomated safety check: PassMIT

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Works with

Categories

Questions about Safe AI Dlc

What does Safe AI Dlc do?

Plan and run programs using the SAFe x AI-DLC fusion. An agent skill from bybren-llc/safe-agentic-workflow. Safe AI Dlc is an agent skill from bybren-llc/safe-agentic-workflow. Plan and run programs using the SAFe x AI-DLC fusion.

When should I use Safe AI Dlc?

Safe AI Dlc fits situations like: turning an audit; initiative into tracker structure (initiative; organizing work as Units of Work and Bolts; wiring a dependency DAG.

How do I install Safe AI Dlc in Claude Code?

Run `npx skills add bybren-llc/safe-agentic-workflow --skill safe-ai-dlc -a claude-code`. Or copy the skill folder (.agents/skills/safe-ai-dlc in bybren-llc/safe-agentic-workflow) into .claude/skills/safe-ai-dlc in your project. Claude Code loads it when a task matches its description.

How do I install Safe AI Dlc in Codex?

Run `npx skills add bybren-llc/safe-agentic-workflow --skill safe-ai-dlc -a codex`. Or copy the skill folder (.agents/skills/safe-ai-dlc in bybren-llc/safe-agentic-workflow) into .agents/skills/safe-ai-dlc in your project. Codex loads it when a task matches its description.

Can I use Safe AI Dlc in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add bybren-llc/safe-agentic-workflow --skill safe-ai-dlc -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/safe-ai-dlc, .gemini/skills/safe-ai-dlc, .github/skills/safe-ai-dlc and .opencode/skills/safe-ai-dlc in your project.

What does Safe AI Dlc need to run?

SKILL.md names no scripts, command-line tools or credentials: Safe AI Dlc is instructions for the agent only.

Does Safe AI Dlc access the network?

SKILL.md names 1 domain. As links in the text: aws.amazon.com. This is read from the text; nothing was executed.

Is Safe AI Dlc safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Safe AI Dlc use?

Safe AI Dlc is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Safe AI Dlc use?

About 1.9k tokens (SKILL.md is roughly 7.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Safe AI Dlc?

Skills that share tags, products or a category with Safe AI Dlc: Coherence Auditor (GoogleChrome/modern-web-guidance-src, 1.1k stars), Mps Project Management (JetBrains/MPS, 1.7k stars), Init My Project (MCSLTeam/MCServerLauncher-Future, 121 stars) and Gh Issues (serejaris/personal-corp-os, 229 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Safe AI Dlc?

bybren-llc (a GitHub organization) maintains it in bybren-llc/safe-agentic-workflow, which has 423 GitHub stars. The repository holds 42 skills in this directory. The repository was last updated on July 20, 2026.

Source: bybren-llc/safe-agentic-workflow on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.