edd-do

edd-do is a skill for Claude Code, Codex from djscheuf/agentic-dev-ecosystem-template. It costs 48 tokens per session (1,254 once invoked), scanned A, original, MIT.

A controlled editing step in an EDD refinement process. EDD here means iteratively improving an agent skill using a plan and evaluation results.

In plain words
What is it for?
Use it to apply one planned change to a skill, its supporting documents, or its evaluation suite after the planning step.
Why use it?
It prevents an improvement pass from changing files outside its approved scope or making an unapproved evaluation change. It also avoids running shell commands during the edit.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: installed under .agents/ (shared by several agents).

Good fit Use it to apply one planned change to a skill, its supporting documents, or its evaluation suite after the planning step.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/djscheuf/agentic-dev-ecosystem-template/edd-do
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 djscheuf/agentic-dev-ecosystem-template --skill edd-do
Clone the repo
git clone --depth 1 https://github.com/djscheuf/agentic-dev-ecosystem-template

Made for: Claude Code, Codex.

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 edd-do

README.md
[![agentmods](https://agentmods.dev/badge/skills/djscheuf/agentic-dev-ecosystem-template/edd-do/github.svg)](https://agentmods.dev/skills/djscheuf/agentic-dev-ecosystem-template/edd-do)
Your own site
<a href="https://agentmods.dev/skills/djscheuf/agentic-dev-ecosystem-template/edd-do"><img src="https://agentmods.dev/badge/skills/djscheuf/agentic-dev-ecosystem-template/edd-do/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 edd-do

Your own site · 80×15
<a href="https://agentmods.dev/skills/djscheuf/agentic-dev-ecosystem-template/edd-do"><img src="https://agentmods.dev/badge/skills/djscheuf/agentic-dev-ecosystem-template/edd-do.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 48 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,254 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.
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 $0.00048 $0.01254
Opus 5.5 $0.00019 $0.00502
Sonnet 5.5 $0.00010 $0.00251
Haiku 4.5 $0.00005 $0.00125

Measured 22d ago against content hash 6e3e825d0c2f, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

edd-do 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 22d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (verify.sh, verify.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.

.agents/skills/edd-do/SKILL.md · 133 lines

How it starts

The opening of the file, as written. The whole thing — 133 lines — stays where its author put it; the contents beside it link to each section on GitHub.

EDD-Do

Purpose

Apply exactly one planned refinement action to a target skill and/or its evaluation suite. Make only the change described in the plan.

No shell commands. Do not run shell commands (exec, git, npm, etc.) — every needed check is either a file edit or a re-read. The workflow runs validation (scope checks, the full evaluation) deterministically after this skill completes.

Prerequisites

  • iterations/<n>/plan.json exists and names an authorized action, intended_files, and expected_effect.
  • The target repository worktree has no stray edits from a previous, not-yet-committed-or-reverted attempt.
  • If action is propose_evaluation_expectation_change, approval has already been recorded for this exact proposal. If it has not, STOP and report this to chat instead of proceeding — never apply an unapproved expectation change.

Workflow Steps

Step 1: Read the Plan

Read iterations/<n>/plan.json:
- action
- intended_files
- rationale
- expected_effect
- iteration_start_baseline

Read refinement.yaml's latest section for full narrative context and any
"changes made" notes left by a prior, related iteration.

Step 2: Load Skill and Eval Context

Read the target skill's SKILL.md / prompt and any supporting documents
named in intended_files.

If the change touches promptfooconfig.yaml, test YAML, custom
assertion/transform JS, or fixtures:
  → Consult the `promptfoo` skill FIRST.
  → Use its phase map to jump to the specific section needed
  instead of guessing at syntax or option names.

Step 3: Make the Minimal Change

Modify ONLY the files listed in intended_files.

By action type:

- refine_skill:
    Edit only the prompt/instruction sections implicated by the
    failure evidence in the plan. Do not rewrite unrelated sections.

- repair:
    Fix the fixture/assertion/helper defect without lowering the bar
    the evaluation is meant to enforce. Prefer fixing an internally
    inconsistent fixture over relaxing an assertion. If the true cause
    is a helper bug (e.g. `||` treating `0` as falsy), fix the helper,
    not the test data.

- add_coverage:
    Add the missing required test case(s). Prefer an existing,
    already-rich fixture over authoring a new one; follow the target
    skill's own fixture-naming and YAML-block conventions (copy an
    existing block, change only what differs).

- refine_supporting_docs:
    Edit only the referenced/example/template document(s) named in
    intended_files.

- propose_evaluation_expectation_change:
    Change only the approved expectation, exactly as approved. Adhere to the approved diff, other changes are forbidden

- Editing a file not listed in intended_files IS FORBIDDEN  
- Refactoring, renaming, or "improving" anything the plan did not ask for IS FORBIDDEN
- Weakening an expectation to make a failure disappear instead of
  fixing the underlying fixture, helper, or skill behavior IS FORBIDDEN

Read the full file on GitHub · 133 lines

Files

What ships with it

4 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. 22d ago First seen · 133 lines · 48 tokens per session scan A 6e3e825d0c2f

Subscribe to this mod's changes

edd-do is a skill published in the GitHub repository djscheuf/agentic-dev-ecosystem-template (12 stars, last pushed 20d ago), licensed MIT. It adds 48 tokens to every session and 1,254 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 2026-10-01.

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