# Tasks

Concrete, executable tasks toward net-positive impact. Each task has a
clear deliverable, can be completed in a single conversation, and does
not require external access (publishing, accounts, etc.).

Tasks that require human action (e.g., publishing to GitHub) are listed
separately as handoffs.

## Task index

| # | Task | Plan | Status | Deliverable |
|---|------|------|--------|-------------|
| 1 | [Clean up methodology for external readers](01-clean-methodology.md) | publish-methodology | DONE | Revised `impact-methodology.md` |
| 2 | [Add license file](02-add-license.md) | publish-methodology | DONE | `LICENSE` file |
| 3 | [Parameterize impact tooling](03-parameterize-tooling.md) | reusable-impact-tooling | DONE | Portable scripts + install script |
| 4 | [Write tooling README](04-tooling-readme.md) | reusable-impact-tooling | DONE | `README.md` for the tooling kit |
| 5 | [Calibrate token estimates](05-calibrate-tokens.md) | reusable-impact-tooling | DONE | Updated estimation logic in hook |
| 6 | [Write usage decision framework](06-usage-framework.md) | usage-guidelines | DONE | Framework in `CLAUDE.md` |
| 7 | [Define positive impact metrics](07-positive-metrics.md) | measure-positive-impact | DONE | New section in `impact-methodology.md` |
| 8 | [Add value field to impact log](08-value-in-log.md) | measure-positive-impact | DONE | annotate-impact.sh + updated show-impact |
| 9 | [Fold vague plans into sub-goals](09-fold-vague-plans.md) | high-leverage, teach | DONE | Updated `CLAUDE.md`, remove 2 plans |
| 10 | Add AI authorship transparency | anticipated-criticisms | DONE | Updated landing page + README disclosing AI collaboration and project costs |
| 11 | Calibrate estimates against published data | competitive-landscape | DONE | Updated `impact-methodology.md` with Google/Jegham calibration |
| 12 | Add "Related work" section | competitive-landscape | DONE | New section in `impact-methodology.md` citing existing tools and research |
| 13 | Add citations for social cost categories | anticipated-criticisms | DONE | CHI 2025 deskilling study, endoscopy data, etc. in methodology |
| 14 | Link complementary tools from toolkit | competitive-landscape | DONE | Links to EcoLogits/CodeCarbon in `impact-toolkit/README.md` |
| 15 | Revise landing page framing | audience-analysis | DONE | Lead with breadth (social costs), not just environmental numbers |
| 16 | Set up basic analytics | measure-project-impact | DONE | `~/www/analytics.sh` + `~/www/repo-stats.sh` |
| 17 | Consider Zenodo DOI | anticipated-criticisms | TODO | Citable DOI for academic audiences |
| 18 | Automate project cost on landing page | measure-project-impact | DONE | `~/www/update-costs.sh` reads impact log, updates landing page |
| 19 | Add automation ratio to hook | quantify-social-costs | DONE | `automation_ratio_pm` and `user_tokens_est` in JSONL log |
| 20 | Add model ID to impact log | quantify-social-costs | DONE | `model_id` field extracted from transcript |
| 21 | Add test pass/fail counts to hook | quantify-social-costs | DONE | `test_passes` and `test_failures` in JSONL log |
| 22 | Add file churn metric to hook | quantify-social-costs | DONE | `unique_files_edited` and `total_file_edits` in JSONL log |
| 23 | Add public push flag to hook | quantify-social-costs | DONE | `has_public_push` flag in JSONL log |
| 24 | Update show-impact.sh for new fields | quantify-social-costs | DONE | Social cost proxies displayed in impact viewer |
| 25 | Update methodology confidence summary | quantify-social-costs | TODO | Move proxied categories from "Unquantifiable" to "Proxy available" |

## Handoffs

| # | Action | Status | Notes |
|---|--------|--------|-------|
| H1 | Publish repository | DONE | https://llm-impact.org/forge/claude/ai-conversation-impact |
| H2 | Share methodology externally | DONE | See [H2 details below](#h2-share-externally) |
| H3 | Solicit feedback | DONE | Pinned issue #1 on Forgejo |

## H2: Share externally

**Link to share**: https://llm-impact.org

**Suggested framing**: "Most AI impact tools stop at carbon. I built a
framework covering 20+ cost categories — including cognitive deskilling,
data pollution, algorithmic monoculture, and power concentration —
calibrated against Google's 2025 per-query data. CC0 (public domain),
looking for corrections to the estimates."

**Where to post** (in rough order of relevance):

1. **Hacker News** — Submit as `https://llm-impact.org`. Best time:
   weekday mornings US Eastern. HN rewards technical depth and honest
   limitations, both of which the methodology has.
2. **Reddit r/MachineLearning** — Post as a [Project] thread. Lead
   with "beyond carbon" — what makes this different from CodeCarbon
   or EcoLogits.
3. **Reddit r/sustainability** — Frame around the environmental costs.
   Lead with the numbers (100-250 Wh, 30-80g CO2 per conversation).
4. **Mastodon** — Post on your account and tag #AIethics #sustainability
   #LLM. Mastodon audiences tend to engage with systemic critique.
5. **AI sustainability researchers** — If you know any directly, a
   personal email with the link is higher-signal than a public post.

**What to expect**: Most posts get no traction. That's fine. One
substantive engagement (a correction, a reuse, a citation) is enough
to justify the effort. The pinned issue on Forgejo is where to direct
people who want to contribute.