agentmods.dev

run-feature-workflow

A structured workflow for implementing a feature from its specification and configuration. It adjusts the amount of planning to the feature's risk and keeps code, tests, documentation, and project records aligned.

In plain words
What is it for?
Use it to load a feature's specification, determine its risk, follow repository architecture rules, update the implementation and tests, and complete the required workflow records.
Why use it?
It gives feature work a repeatable process and reduces the chance that implementation, tests, or required project documents fall out of sync.

Skill for Claude CodeCodexCursor

2 1mo ago A scan 12 tokens copy · 92% MIT
View the source file markmhendrickson/foundation
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/markmhendrickson/foundation/run-feature-workflow
Any agent
npx skills add markmhendrickson/foundation --skill run-feature-workflow
Clone the repo
git clone --depth 1 https://github.com/markmhendrickson/foundation

Made for: Claude Code, Codex, Cursor.

Per session 12 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 700 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 92% copy Near-identical to another mod 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 $0.00012 $0.00700
Opus 5 $0.00006 $0.00350
Sonnet 5 $0.00002 $0.00140
Haiku 4.5 $0.00001 $0.00070

Measured 2d ago against content hash bdd57b380843, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

run-feature-workflow 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.

Origin

This is a copy

92% identical to run-feature-workflow — 7 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.cursor/skills/run-feature-workflow/SKILL.md · 80 lines

How it starts

The opening of the file, as written. The whole thing — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Run Feature Workflow

feature_id = {{input:feature_id}}

Configuration is read from foundation-config.yaml.

  1. Load configuration:

    • Read foundation-config.yaml to get feature unit settings
    • Determine directory structure, manifest complexity, testing requirements

  2. Read authoritative documents:

    • foundation/development/feature_unit_workflow.md (workflow context)
    • {configured_directory}/in_progress/{{input:feature_id}}/{{input:feature_id}}_spec.md (or completed/ if completed)
    • {configured_directory}/in_progress/{{input:feature_id}}/manifest.yaml (or completed/ if completed)
    • foundation/development/templates/feature_unit_spec_template.md
    • Repository-specific execution instructions (if they exist)
    • Repository-specific architecture/module documentation (based on spec)

  3. Determine risk level:

    • low → skip plan
    • medium → produce brief structured plan
    • high/critical → produce detailed plan and wait for user approval

  4. Apply Feature Unit execution principles:

    • Update spec/manifest if ambiguous
    • Update code/tests/docs together
    • Follow architectural invariants (from repo-specific docs)
    • Preserve accessibility and i18n rules (if applicable)

  5. Run tests (based on configuration):

    • Unit tests (if testing.require_unit_tests: true)
    • Integration tests (if testing.require_integration_tests: true)
    • E2E tests (if testing.require_e2e_tests: true)
    • Verify coverage meets configured targets

    If any tests fail:

    • Immediately invoke Fix Feature Bug with feature_id={{input:feature_id}}
    • Do NOT attempt to fix bugs inline
    • Let the error protocol classify and correct
    • After bugfix completes, re-run the test suite
    • Only proceed to step 6 once all tests pass

  6. Apply error protocol (if repository has one) only if bugs were encountered and fixed via step 5.

  7. Spec-to-Implementation Diff Checkpoint (CRITICAL):

    Before producing the final summary:

    • Compare the implemented code against the spec
    • List any ways implementation intentionally diverged from spec (even if small)
    • For each divergence:
      • Either update the spec to reflect the change (if divergence is intentional and correct)
      • Or mark the divergence as a bug to be fixed (if divergence is unintentional)
    • Present this diff to the user:
      • "Implementation vs Spec Diff: [list of divergences]"
      • "For each divergence, should I update the spec or fix the implementation? (spec/implementation/list)"
    • Do NOT proceed to final summary until spec and implementation are aligned (either by updating spec or fixing implementation)

  8. Produce a final change summary:

    • feature_id
    • files changed
    • risk
    • error_class (if bugfix)
    • tests run
    • coverage achieved

Read the full file on GitHub · 80 lines

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. 2d ago First seen · 80 lines · 12 tokens per session scan A bdd57b380843

Subscribe to this mod's changes

run-feature-workflow is a skill published in the GitHub repository markmhendrickson/foundation (2 stars, last pushed 1mo ago), licensed MIT. It adds 12 tokens to every session and 700 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to run-feature-workflow, differing in 7 lines, and is treated as a copy.

Planning
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