operational-value-designer

Guidance for building a fixed, repeatable grader that measures how much a GitHub Agentic Workflow achieved its intended repository result.

In plain words
What is it for?
Use it to create an executable operational-value grader, configure it in a workflow, and report attainment and optional comparison with a baseline.
Why use it?
It separates the result actually accepted in the repository from execution quality, output amount, or the agent's own opinion.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/github/gh-aw/operational-value-designer
Any agent
npx skills add github/gh-aw --skill operational-value-designer
Clone the repo
git clone --depth 1 https://github.com/github/gh-aw

Made for: Claude Code, Codex.

Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,774 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00060 $0.01774
Opus 5 $0.00030 $0.00887
Sonnet 5 $0.00012 $0.00355
Haiku 4.5 $0.00006 $0.00177

Measured today against content hash 1013d299ea56, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

operational-value-designer 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 today.

The scan reads SKILL.md. This mod also ships 3 executable files (scripts/operational-value-evaluator-path.sh, scripts/verify-operational-value-evaluator.sh, tests/test.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

.github/skills/operational-value-designer/SKILL.md · 150 lines

How it starts

The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Operational Value Grader

Design one deterministic operational-value grader that reports absolute operational attainment for each workflow run. Keep exactly one authoritative primary value, and declare any normalized diagnostic metrics separately.

Operational value is the degree to which the workflow's intended repository outcome is attained for the opportunity assigned to a run, demonstrated by accepted repository evidence under a frozen contract. It is not execution quality, output volume, safe-output creation, or an agent's assessment.

Output

Create one executable evaluator at:

.github/graders/WORKFLOW-NAME-operational-value.sh

Configure the workflow:

graders:
  operational-value:
    run: .github/graders/WORKFLOW-NAME-operational-value.sh

The grader's primary operational value (value) is absolute attainment in [0,1]. A comparable frozen baseline may be reported separately as baselineValue; gh-aw derives deltaFromBaseline. Never define the primary operational value as a difference from baseline.

Design Procedure

  1. Validate OWNER/REPO and resolve .github/workflows/WORKFLOW-NAME.md. Do not infer inputs from the workspace or remotes.
  2. Recover adoption-time intent from the workflow's first commit and first parent. Use only adoption-time workflow content and pre-adoption evidence to choose opportunities, accepted evidence, formulas, targets, or a baseline.
  3. Define how every workflow run binds to one operational case:
    • produce a stable opportunityKey;
    • prevent overlapping ownership where possible;
    • preserve repeated keys when duplicate runs target the same opportunity so downstream analysis can cluster or deduplicate them;
    • treat reruns with the same GitHub run ID as the same subject.
  4. Freeze accepted evidence, evidence repositories, matching rules, zero-versus-missing behavior, and maturesAt computation.
  • Declare only the workflow permission scopes required to collect that evidence. The evaluator receives GH_TOKEN with the agent job's declared permissions; gh-aw does not add evidence permissions automatically.
  1. Choose exactly one direct primary metric in [0,1]. Higher must always mean greater attainment. Optional diagnostic metrics may provide normalized outcome context, but must remain separate rather than being combined into the primary value. Keep trace graders and activity counts separate.
  2. If comparable pre-adoption evidence exists, score it with the same metric and freeze it under baseline. Otherwise use attainment-only with a null baseline value.
  3. Implement the evaluator interface below and run:

Read the full file on GitHub · 150 lines

Files

What ships with it

3 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. today Changed · +16 lines 1013d299ea56
  2. 2d ago First seen · 134 lines · 60 tokens per session scan A fbcc6e3efa06

Subscribe to this mod's changes

operational-value-designer is a skill published in the GitHub repository github/gh-aw (5,084 stars, last pushed today), licensed MIT. It adds 60 tokens to every session and 1,774 once invoked, about $0.0003 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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