community-sweep
Land community pull requests as the contributor and answer community issues on thedotmack/claude-mem. Takes stock of every open…
Believable agent cost report for any period, default the last 7 full days PT, not counting today. Measured tokens from Claude Code transcripts priced at OpenRouter list prices (ESTIMATED), measured provider spend when a sanctioned source exists, note-taker cost separate,
Claude Code
$ npx -y skills add thedotmack/claude-mem --skill agent-cost-report --agent claude-code
Codex
$ npx skills add thedotmack/claude-mem --skill agent-cost-report -a codex -y
Cursor
$ npx skills add thedotmack/claude-mem --skill agent-cost-report -a cursor -y
Gemini CLI
$ npx skills add thedotmack/claude-mem --skill agent-cost-report -a gemini-cli -y
GitHub Copilot
$ npx skills add thedotmack/claude-mem --skill agent-cost-report -a github-copilot -y
OpenCode
$ npx skills add thedotmack/claude-mem --skill agent-cost-report -a opencode -y
Windsurf
$ npx skills add thedotmack/claude-mem --skill agent-cost-report -a windsurf -y
name: Agent Cost Report description: >- Believable agent cost report for any period, default the last 7 full days PT, not counting today. Measured tokens from Claude Code transcripts priced at OpenRouter list prices (ESTIMATED), measured provider spend when a sanctioned source exists, note-taker cost separate, Timing-style HTML/PDF plus report.json, line-items.csv, evidence.json. allowed-tools: - Bash - Read - Write - AskUserQuestion - mcp__plugin_claude-mem_mcp-search__search - mcp__plugin_claude-mem_mcp-search__timeline - mcp__plugin_claude-mem_mcp-search__get_observations
**Claude-Mem / Claude Code skill.** Runtime is the `scripts/` pipeline (transcripts → tokens → dollars → Timing-style report) plus a progressive Mem Search review pass that confirms the drafted labels. The Notion draft is SPEC history only — never the product, never the runtime, never the ship vehicle.
Resolve the absolute directory containing this `SKILL.md`; all helper paths are relative to that directory. `${CLAUDE_SKILL_DIR}` is the shortcut: `python3 "${CLAUDE_SKILL_DIR}/scripts/acr.py" …`. Python 3.9+ standard library only, with IANA timezone data for `America/Los_Angeles`; no pip installs. `tzdata` is the only exception to the no-pip-installs rule, and only when `acr.py` exits saying that timezone data is unavailable (stock Windows Python ships none): show the user the lines it printed and ask (AskUserQuestion) before installing it. On a yes, run the line for your shell (the plain quoted line in Bash or cmd, the `PowerShell:` line in PowerShell), then rerun the failed command. Setting `PYTHONTZPATH` instead needs no install. The look lives in `scripts/acr/render.py`, never here.
Turn Claude-Mem activity into a **manager-readable cost and failure report**.
Product idea: a reusable skill that searches Claude-Mem via Mem Search, reconstructs real units of work, assigns cost and failure categories, and renders a printable report.
The headline is dollars, to two decimals, labeled. The dollars come from Claude Code transcripts (exact per-reply token usage) priced at OpenRouter public list prices, so they are **ESTIMATED**. Measured provider spend appears only when a sanctioned source gives it. Directly under the dollars: what the mistakes cost, what shipped, and both on one time axis.
1. What work was completed? 2. What did each outcome cost? 3. What was wasted through looping, hedging, wrong turns, rework, or poor routing? 4. Were any unauthorized actions attempted? 5. What should the manager change next?
**Primary unit = cost per completed outcome** (not cost per observation).
Memory dig mechanics: the claude-mem `mem-search` skill (progressive recall).
Follow the claude-mem `mem-search` three layers. Keep spend light.
1. **Search** — get an index of IDs (titles, types, token hints). 2. **Timeline** — only around anchors you care about. 3. **Observations** — `get_observations` for the filtered IDs you will cite as evidence.
Recipe:
1. Resolve scope (default: the last 7 full PT days). 2. Search → collect IDs. 3. Timeline for thin context only. 4. Observations for intended / actual / outcome / waste / rework / blocked / unauthorized / status. 5. Group into named work items + failure events. 6. Calculate line-item costs. 7. Render HTML + optional PDF (+ json/csv/evidence). 8. Keep evidence IDs in the appendix — do not dump entire timelines into the main report.
ADHD process bullets:
In this skill the search pass is the **review step** (see Recipe step 4): the pipeline drafts categories and failure types from keywords (`label_source: keyword`); the orchestrator confirms or changes each line item's `category` and `failure_type` from its cited evidence IDs and applies the result with `review --apply`. Items left unreviewed keep the "draft label" mark and the footer counts them.
`Feature` · `Bug fix` · `Incident` · `Maintenance` · `Investigation` · `Experiment`
`Looping` · `Hedging` · `Wrong turn` · `Rework` · `Regression` · `Premature completion` · `Unauthorized action` · `Suboptimal path` · `Duplicate work` · `Blocked work` · `Missed requirement` · `Unnecessary escalation` · `Context re-read` · `Model thrash` · `Fan-out waste` · `Recovery after miss`
**Rework lock (ALWAYS):** Rework lives **only** under `failure_type` — never as a work category. Keep category as the intended job type; set `failure_type: Rework` when rework occurred.
A line item can have a work category **
Persistent Context Across Sessions for Every Agent – Captures everything your agent does during sessions, compresses it with AI, and injects relevant context back into future sessions. Works with Claude Code, OpenClaw, Codex, Gemini, Hermes, Copilot, OpenCode + More
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