efficiency-metrics

efficiency-metrics is a skill for Claude Code from dhslegen/digital-delivery-team. It costs 30 tokens per session (1,422 once invoked), scanned A, original, MIT.

A guide for measuring project effort, quality, and efficiency against a fixed baseline. It combines time from comparable past projects with independent expert estimates before implementation begins.

In plain words
What is it for?
Use it to create locked baselines, compare planned and actual hours by project stage, check quality gates, and write an evidence-linked efficiency report.
Why use it?
It makes it easier to see where work became faster or slower without changing the comparison after the fact. It also flags quality deterioration using coverage, review issues, acceptance, rework, and defect measures.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths.

Part of the digital-delivery-team plugin — 13 skills, 21 commands, 9 agents, 8 hooks shipped together

Good fit Use it to create locked baselines, compare planned and actual hours by project stage, check quality gates, and write an evidence-linked efficiency report.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/dhslegen/digital-delivery-team/efficiency-metrics
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 dhslegen/digital-delivery-team --skill efficiency-metrics
Clone the repo
git clone --depth 1 https://github.com/dhslegen/digital-delivery-team

Made for: Claude Code.

Or install digital-delivery-team, the plugin that ships this one along with the rest of its 13 skills, 21 commands, 9 agents, 8 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 efficiency-metrics

README.md
[![agentmods](https://agentmods.dev/badge/skills/dhslegen/digital-delivery-team/efficiency-metrics/github.svg)](https://agentmods.dev/skills/dhslegen/digital-delivery-team/efficiency-metrics)
Your own site
<a href="https://agentmods.dev/skills/dhslegen/digital-delivery-team/efficiency-metrics"><img src="https://agentmods.dev/badge/skills/dhslegen/digital-delivery-team/efficiency-metrics/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 efficiency-metrics

Your own site · 80×15
<a href="https://agentmods.dev/skills/dhslegen/digital-delivery-team/efficiency-metrics"><img src="https://agentmods.dev/badge/skills/dhslegen/digital-delivery-team/efficiency-metrics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,422 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 $0.00030 $0.01422
Opus 5 $0.00015 $0.00711
Sonnet 5 $0.00006 $0.00284
Haiku 4.5 $0.00003 $0.00142

Measured 9d ago against content hash f515a0f127c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

efficiency-metrics 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 9d 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.

skills/efficiency-metrics/SKILL.md · 88 lines

How it starts

The opening of the file, as written. The whole thing — 88 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Efficiency Metrics

Triggers

  • metrics-agent 启动 / /report 命令

Baseline 双口径(必须同时产生)

管道 A:历史同类项目工时

  • 从最近 6 个月的真实项目里选 3–5 个可比案例
  • 按阶段(需求 / 架构 / 前端 / 后端 / 联调 / 测试 / 文档)拆解实际工时
  • 存入 baseline/historical-projects.csv(见模板格式)

管道 B:专家独立估算

  • 架构师 + 项目经理各自独立估算(禁止在 PRD 之后参考任何实际产物)
  • 两人估算差 > 20% → 开一次对齐会,消除差异
  • 存入 baseline/estimation-rules.md

最终 baseline = 两者均值

  • 封盘时机:/prd + /wbs 产出后、/impl 启动前
  • 封盘命令:先解析 DDT_PLUGIN_ROOT;若 baseline/baseline.locked.json 不存在,再执行 node "$DDT_PLUGIN_ROOT/bin/baseline.mjs" --lock --hist baseline/historical-projects.csv --expert baseline/estimation-rules.md --out baseline/baseline.locked.json
  • 封盘后禁止修改(防止后视偏差污染对比数据)
  • baseline/baseline.locked.json 属于被交付项目目录,不属于插件源码目录

质量守门阈值(任一劣化即在报告首行标红 ⚠️)

  • 覆盖率(branch)≥ 70%
  • Review 阻塞级问题 = 0
  • 验收标准通过率 = 100%
  • 返工次数(相对基线)不上升
  • 缺陷密度不上升

Report Structure(硬性,不可省略任一章节)

  1. 摘要:一句话结论 + ⚠️ 劣化告警(若有,必须是报告第一行)
  2. 阶段级对比表: | 阶段 | 基线(h) | 实际(h) | 节省(h) | 提效% | (按"提效%"降序排,负值表示劣化)
  3. 质量守门表:覆盖率 / 阻塞级 / 验收通过率 / 返工次数 / 缺陷密度
  4. 三个分析问题的回答
    • 哪个阶段提效最多?为什么?
    • 哪个阶段提效最少或劣化?根因是什么?
    • 下次怎么优化?给出 ≤ 3 条可执行建议
  5. Top 3 优化建议(必须可执行,不能是"加强 XX")
  6. 原始数据链接:events.jsonl 路径 + metrics.db dump 命令

数据链路(hooks → 脚本 → 报告)

hooks → ~/.claude/delivery-metrics/events.jsonl → bin/aggregate.mjs → metrics.db ┐
                                                                                  ├→ bin/report.mjs → docs/efficiency-report.raw.md
baseline/historical-projects.csv + baseline/estimation-rules.md                  │
      → bin/baseline.mjs → baseline/baseline.locked.json ────────────────────────┘
docs/efficiency-report.raw.md → metrics-agent → docs/efficiency-report.md

events.jsonl 字段结构:

{"event":"session_start","ts":"2026-01-01T00:00:00Z","project_id":"<id>","data":{"session_id":"<uuid>","cwd":"<path>"}}
{"event":"session_end","ts":"2026-01-01T01:00:00Z","project_id":"<id>","data":{"session_id":"<uuid>","tokens_input":1000,"tokens_output":500}}
{"event":"pre_tool_use","ts":"2026-01-01T00:10:00Z","project_id":"<id>","data":{"session_id":"<uuid>","tool_name":"Write","file_path":"docs/prd.md"}}
{"event":"post_tool_use","ts":"2026-01-01T00:10:02Z","project_id":"<id>","data":{"session_id":"<uuid>","tool_name":"Write","success":true,"output_size":2048}}
{"event":"subagent_stop","ts":"2026-01-01T00:30:00Z","project_id":"<id>","data":{"session_id":"<uuid>","subagent_name":"product-agent","duration_ms":120000,"tokens_input":1000,"tokens_output":500}}
{"event":"quality_metrics","ts":"2026-01-01T00:40:00Z","project_id":"<id>","data":{"defects_critical":0,"defects_major":1,"defects_minor":2,"coverage_pct":72.5,"rework_count":0,"acceptance_pass_pct":100}}

Read the full file on GitHub · 88 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. 9d ago First seen · 88 lines · 30 tokens per session scan A f515a0f127c8

Subscribe to this mod's changes

efficiency-metrics is a skill published in the GitHub repository dhslegen/digital-delivery-team (1 stars, last pushed 3mo ago), licensed MIT. It adds 30 tokens to every session and 1,422 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 2026-08-31.

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