commission

commission is a skill for Claude Code from SteveGJones/ai-first-sdlc-practices. It costs 49 tokens per session (1,219 once invoked), scanned A, original, MIT.

A guided setup that assigns a project to an SDLC option, meaning a software-development process suited to its team size and regulatory needs.

In plain words
What is it for?
Use it to select a solo, single-team, programme, or regulated-project process, install its supporting bundle, and save the decision in the project configuration.
Why use it?
It helps choose and record an appropriate level of process instead of leaving team responsibilities and required checks unclear.

Skill for Claude Code

Written for Claude Code: disable-model-invocation in frontmatter.

Part of the sdlc-core plugin — 10 skills, 5 agents, 2 hooks shipped together

Good fit Use it to select a solo, single-team, programme, or regulated-project process, install its supporting bundle, and save the decision in the project configuration.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/stevegjones/ai-first-sdlc-practices/commission
Install

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.

Any agent
npx skills add SteveGJones/ai-first-sdlc-practices --skill commission
Clone the repo
git clone --depth 1 https://github.com/SteveGJones/ai-first-sdlc-practices

Made for: Claude Code.

Or install sdlc-core, the plugin that ships this one along with the rest of its 10 skills, 5 agents, 2 hooks.

Wrote 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.

agentmods badge for commission

README.md
[![agentmods](https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/commission/github.svg)](https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/commission)
Your own site
<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/commission"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/commission/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.

agentmods 80×15 button for commission

Your own site · 80×15
<a href="https://agentmods.dev/skills/stevegjones/ai-first-sdlc-practices/commission"><img src="https://agentmods.dev/badge/skills/stevegjones/ai-first-sdlc-practices/commission.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 49 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,219 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00049 $0.01219
Opus 5 $0.00024 $0.00609
Sonnet 5 $0.00010 $0.00244
Haiku 4.5 $0.00005 $0.00122

Measured 10d ago against content hash 8ff98da94e1c, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

commission 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 10d 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.

plugins/sdlc-core/skills/commission/SKILL.md · 148 lines

How it starts

The opening of the file, as written. The whole thing — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Commission an SDLC Option Bundle

Walk a project through commissioning to one of four SDLC options: solo (1-2 people, fast iteration), single-team (3-10, current default), programme (11-50, formal phase gates), assured (regulated industries with traceability).

Pre-flight

PROJECT_DIR=$(pwd)
TEAM_CONFIG="$PROJECT_DIR/.sdlc/team-config.json"

# Check if already commissioned
python3 -c "
from pathlib import Path
from sdlc_core_scripts.commission.recorder import is_commissioned
print('COMMISSIONED' if is_commissioned(Path('$TEAM_CONFIG')) else 'FRESH')
"

If COMMISSIONED, ask the user to confirm re-commissioning before proceeding. Show the existing record:

python3 -c "
from pathlib import Path
from sdlc_core_scripts.commission.recorder import read_record
r = read_record(Path('$TEAM_CONFIG'))
print(f'  Current option: {r.sdlc_option}')
print(f'  Current level: {r.sdlc_level}')
print(f'  Bundle version: {r.option_bundle_version}')
print(f'  Commissioned: {r.commissioned_at} by {r.commissioned_by}')
"

Questions (ask one at a time, brief)

Skip any question whose answer is in arguments (--option, --level).

  1. Team size — 1-2 / 3-10 / 11-50 / 50+
  2. Blast radius of a defect — low / moderate / high / severe
  3. Regulatory burden — none / low / moderate / high
  4. Specification maturity — emergent / mixed / contract-first / formal
  5. Time-to-market pressure — very high / high / moderate / low

If user has set arguments overriding all of these, skip directly to recommendation.

Recommendation logic

team-size 1-2 + low blast radius          → solo / prototype
team-size 3-10 + moderate blast radius    → single-team / production
team-size 11-50 + formal spec             → programme / production
any size + high regulatory burden         → assured / enterprise

If two recommendations tie, prefer the simpler one (solo > single-team > programme > assured).

Show the recommendation with rationale (which questions drove it).

Read the full file on GitHub · 148 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 10d ago First seen · 148 lines · 49 tokens per session scan A 8ff98da94e1c

Subscribe to this mod's changes

commission is a skill published in the GitHub repository SteveGJones/ai-first-sdlc-practices (41 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 1,219 once invoked, about $0.0002 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.

Related

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