plan-to-issues-csv

plan-to-issues-csv is a skill for Claude Code, Codex from midFang/ai-agent-skills-workflow. It costs 124 tokens per session (641 once invoked), scanned A, original, MIT.

A tool that converts a written execution plan into a uniquely named CSV snapshot of trackable issues. A CSV is a plain-text table that spreadsheet programs can open.

In plain words
What is it for?
Use it with a plan Markdown file to create an issues snapshot containing phases, priorities, descriptions, acceptance checks, review requirements, states, ownership, and related fields.
Why use it?
It turns a plan into rows that can be reviewed, maintained, and tracked over time without using one easily overwritten summary file.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: $skill-name invocation.

Good fit Use it with a plan Markdown file to create an issues snapshot containing phases, priorities, descriptions, acceptance checks, review requirements, states, ownership, and related fields.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/midfang/ai-agent-skills-workflow/plan-to-issues-csv
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 midFang/ai-agent-skills-workflow --skill plan-to-issues-csv
Clone the repo
git clone --depth 1 https://github.com/midFang/ai-agent-skills-workflow

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 plan-to-issues-csv

README.md
[![agentmods](https://agentmods.dev/badge/skills/midfang/ai-agent-skills-workflow/plan-to-issues-csv/github.svg)](https://agentmods.dev/skills/midfang/ai-agent-skills-workflow/plan-to-issues-csv)
Your own site
<a href="https://agentmods.dev/skills/midfang/ai-agent-skills-workflow/plan-to-issues-csv"><img src="https://agentmods.dev/badge/skills/midfang/ai-agent-skills-workflow/plan-to-issues-csv/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 plan-to-issues-csv

Your own site · 80×15
<a href="https://agentmods.dev/skills/midfang/ai-agent-skills-workflow/plan-to-issues-csv"><img src="https://agentmods.dev/badge/skills/midfang/ai-agent-skills-workflow/plan-to-issues-csv.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 124 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 641 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 $0.00124 $0.00641
Opus 5 $0.00062 $0.00320
Sonnet 5 $0.00025 $0.00128
Haiku 4.5 $0.00012 $0.00064

Measured 8d ago against content hash 4b2f4a9e436e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

plan-to-issues-csv 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 8d 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.

plan-to-issues-csv/SKILL.md · 68 lines

How it starts

The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Plan To Issues CSV

Use this skill as the replacement for the deprecated custom prompt /prompts:plan_to_issues_csv.

Invocation

Preferred explicit trigger:

  • $plan-to-issues-csv plan/2026-03-31_10-00-00-login-flow.md

Natural-language triggers:

  • 把这个 plan 转成 issues csv
  • 从 plan 生成可维护的 issues 快照

Input Rules

  1. Accept an optional plan file path.
  2. If no path is provided, use the latest plan/*.md in the current workspace.
  3. Read the plan file first, then read only the minimum referenced files needed to fill gaps.

Output Rules

  1. Always write a uniquely named snapshot under issues/.
  2. Never create or update issues/issues.csv, issues.csv, or any other fixed summary CSV.
  3. Write the file as UTF-8 with BOM for Excel compatibility.
  4. Keep the CSV maintainable: default to one issue row per plan phase unless a phase clearly contains multiple independent workstreams.
  5. Target roughly 5-30 rows.

Fixed Header

Use this exact header order:

id,priority,phase,area,title,git_message,description,acceptance_criteria,test_mcp,review_initial_requirements,review_regression_requirements,dev_state,review_initial_state,review_regression_state,git_state,owner,refs,notes

Row Defaults

  • dev_state: 未开始
  • review_initial_state: 未开始
  • review_regression_state: 未开始
  • git_state: 未提交
  • owner: empty
  • notes: empty
  • refs: must not be empty; use path:line and separate multiple refs with ;

Validation

Before finishing:

  1. Ensure the CSV is parseable.
  2. Ensure every row has the full header width.
  3. Ensure all state columns only use the allowed enum values.
  4. Ensure every row has a non-empty refs value.

Reply Shape

Return only the essentials:

  • Snapshot path
  • Row count
  • Any risks such as Excel/WPS file locks or limited source detail
  • The next recommended command in skill form: $plan-csv-execute <snapshot-path>

If file writes are blocked, return the full CSV in a code block and state the target path plus the UTF-8 BOM requirement.

Read the full file on GitHub · 68 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. 8d ago First seen · 68 lines · 124 tokens per session scan A 4b2f4a9e436e

Subscribe to this mod's changes

plan-to-issues-csv is a skill published in the GitHub repository midFang/ai-agent-skills-workflow (2 stars, last pushed 2mo ago), licensed MIT. It adds 124 tokens to every session and 641 once invoked, about $0.0006 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 2026-08-31.

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