tc
Track technical changes with structured records, a state machine, and session handoff. Usage: /tc <init|create|update|status|resume|close|export|dashboard> [args]
Best use case
tc is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Track technical changes with structured records, a state machine, and session handoff. Usage: /tc <init|create|update|status|resume|close|export|dashboard> [args]
Teams using tc should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/tc/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How tc Compares
| Feature / Agent | tc | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Track technical changes with structured records, a state machine, and session handoff. Usage: /tc <init|create|update|status|resume|close|export|dashboard> [args]
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# /tc — Technical Change Tracker
Dispatch a TC (Technical Change) command. Arguments: `$ARGUMENTS`.
If `$ARGUMENTS` is empty, print this menu and stop:
```
/tc init Initialize TC tracking in this project
/tc create <name> Create a new TC record
/tc update <tc-id> [...] Update fields, status, files, handoff
/tc status [tc-id] Show one TC or the registry summary
/tc resume <tc-id> Resume a TC from a previous session
/tc close <tc-id> Transition a TC to deployed
/tc export Re-render derived artifacts
/tc dashboard Re-render the registry summary
```
Otherwise, parse `$ARGUMENTS` as `<subcommand> <rest>` and dispatch to the matching protocol below. All scripts live at `engineering/tc-tracker/scripts/`.
## Subcommands
### `init`
1. Run:
```bash
python3 engineering/tc-tracker/scripts/tc_init.py --root . --json
```
2. If status is `already_initialized`, report current statistics and stop.
3. Otherwise report what was created and suggest `/tc create <name>` as the next step.
### `create <name>`
1. Parse `<name>` as a kebab-case slug. If missing, ask the user for one.
2. Prompt the user (one question at a time) for:
- Title (5-120 chars)
- Scope: `feature | bugfix | refactor | infrastructure | documentation | hotfix | enhancement`
- Priority: `critical | high | medium | low` (default `medium`)
- Summary (10+ chars)
- Motivation
3. Run:
```bash
python3 engineering/tc-tracker/scripts/tc_create.py --root . \
--name "<slug>" --title "<title>" --scope <scope> --priority <priority> \
--summary "<summary>" --motivation "<motivation>" --json
```
4. Report the new TC ID and the path to the record.
### `update <tc-id> [intent]`
1. If `<tc-id>` is missing, list active TCs (status `in_progress` or `blocked`) from `tc_status.py --all` and ask which one.
2. Determine the user's intent from natural language:
- **Status change** → `--set-status <state>` with `--reason "<why>"`
- **Add files** → one or more `--add-file path[:action]`
- **Add a test** → `--add-test "<title>" --test-procedure "<step>" --test-expected "<result>"`
- **Update handoff** → any combination of `--handoff-progress`, `--handoff-next`, `--handoff-blocker`, `--handoff-context`
- **Add a note** → `--note "<text>"`
- **Add a tag** → `--tag <tag>`
3. Run:
```bash
python3 engineering/tc-tracker/scripts/tc_update.py --root . --tc-id <tc-id> [flags] --json
```
4. If exit code is non-zero, surface the error verbatim. The state machine and validator will reject invalid moves — do not retry blindly.
### `status [tc-id]`
- If `<tc-id>` is provided:
```bash
python3 engineering/tc-tracker/scripts/tc_status.py --root . --tc-id <tc-id>
```
- Otherwise:
```bash
python3 engineering/tc-tracker/scripts/tc_status.py --root . --all
```
### `resume <tc-id>`
1. Run:
```bash
python3 engineering/tc-tracker/scripts/tc_status.py --root . --tc-id <tc-id> --json
```
2. Display the handoff block prominently: `progress_summary`, `next_steps` (numbered), `blockers`, `key_context`.
3. Ask: "Resume <tc-id> and pick up at next step 1? (y/n)"
4. If yes, run an update to record the resumption:
```bash
python3 engineering/tc-tracker/scripts/tc_update.py --root . --tc-id <tc-id> \
--note "Session resumed" --reason "session handoff"
```
5. Begin executing the first item in `next_steps`. Do NOT re-derive context — trust the handoff.
### `close <tc-id>`
1. Read the record via `tc_status.py --tc-id <tc-id> --json`.
2. Verify the current status is `tested`. If not, refuse and tell the user which transitions are still required.
3. Check `test_cases`: warn if any are `pending`, `fail`, or `blocked`.
4. Ask the user:
- "Who is approving? (your name, or 'self')"
- "Approval notes (optional):"
- "Test coverage status: none / partial / full"
5. Run:
```bash
python3 engineering/tc-tracker/scripts/tc_update.py --root . --tc-id <tc-id> \
--set-status deployed --reason "Approved by <approver>" --note "Approval: <approver> — <notes>"
```
Then directly edit the `approval` block via a follow-up update if your script version supports it; otherwise instruct the user to record approval in `notes`.
6. Report: "TC-NNN closed and deployed."
### `export`
There is no automatic HTML export in this skill. Re-validate everything instead:
1. Read the registry.
2. For each record, run:
```bash
python3 engineering/tc-tracker/scripts/tc_validator.py --record <path> --json
```
3. Run:
```bash
python3 engineering/tc-tracker/scripts/tc_validator.py --registry docs/TC/tc_registry.json --json
```
4. Report: total records validated, any errors, paths to anything invalid.
### `dashboard`
Run the all-records summary:
```bash
python3 engineering/tc-tracker/scripts/tc_status.py --root . --all
```
## Iron Rules
1. **Never edit `tc_record.json` by hand.** Always use `tc_update.py` so revision history is appended and validation runs.
2. **Never skip the state machine.** Walk forward through states even if it feels redundant.
3. **Never delete a TC.** History is append-only — add a final revision and tag it `[CANCELLED]`.
4. **Background bookkeeping.** When mid-task, spawn a background subagent to update the TC. Do not pause coding to do paperwork.
5. **Validate before reporting success.** If a script exits non-zero, surface the error and stop.
## Related Skills
- `engineering/tc-tracker` — Full SKILL.md with schema reference, lifecycle diagrams, and the handoff format.
- `engineering/changelog-generator` — Pair with TC tracker: TCs for the per-change audit trail, changelog for user-facing release notes.
- `engineering/tech-debt-tracker` — For tracking long-lived debt rather than discrete code changes.Related Skills
wiki-query
Query the LLM Wiki — reads index.md first, drills into 3-10 relevant pages, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back as a new comparison or synthesis page. Usage /wiki-query "<question>"
wiki-log
Show recent entries from the LLM Wiki log (wiki/log.md). Uses the standardized
wiki-lint
Run a health check on the LLM Wiki vault — mechanical checks (orphans, broken links, stale pages, missing frontmatter, log gap, duplicates) plus semantic checks (contradictions, cross-reference gaps, concepts missing their own page). Outputs a markdown report with suggested actions. Usage /wiki-lint [--stale-days N] [--log-gap-days N]
wiki-init
Bootstrap a fresh LLM Wiki vault with the three-layer structure, schema files, and starter templates. Usage /wiki-init <path> --topic "<topic>" [--tool all|claude-code|codex|cursor|antigravity]
wiki-ingest
Ingest a source file from raw/ into the LLM Wiki — read, discuss, write summary page, update cross-references across 5-15 pages, regenerate index, append to log. Usage /wiki-ingest <path-to-source>
tc-tracker
Use when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions. Covers init/create/update/status/resume/close/export workflows for structured code change documentation.
llm-wiki
Use when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
karpathy-coder
Use when writing, reviewing, or committing code to enforce Karpathy's 4 coding principles — surface assumptions before coding, keep it simple, make surgical changes, define verifiable goals. Triggers on "review my diff", "check complexity", "am I overcomplicating this", "karpathy check", "before I commit", or any code quality concern where the LLM might be overcoding.
karpathy-check
Run Karpathy's 4-principle review on staged changes or the last commit. Checks complexity, diff noise, hidden assumptions, and goal verification. Usage /karpathy-check [--last-commit]
cs-wiki-linter
Dispatched sub-agent that runs a periodic health check on an LLM Wiki vault. Runs mechanical checks via scripts (orphans, broken links, stale pages, missing frontmatter, duplicate titles, log gaps), does semantic checks (contradictions, stale claims, cross-reference gaps, concepts missing their own page), and produces a markdown report with suggested actions. Spawn weekly, after batch ingests, or when the user says "check the wiki" / "lint my wiki" / "audit the vault".
cs-wiki-librarian
Dispatched sub-agent that answers queries against an LLM Wiki vault. Reads index.md first, drills into 3-10 relevant pages across categories, synthesizes an answer with inline [[wikilink]] citations, and offers to file the answer back into the wiki as a new comparison or synthesis page. Spawn when the user asks a substantive question the wiki might answer, says "what does the wiki say about X", "compare A and B across my sources", or wants to explore a topic.
cs-wiki-ingestor
Dispatched sub-agent that ingests a new source into an LLM Wiki vault. Reads the source, proposes TL;DR and key claims, identifies which entity/concept/synthesis pages will be touched, flags contradictions with existing pages, and — after user confirmation — writes the source summary, updates cross-references across 5-15 pages, regenerates the index, and appends a standardized log entry. Spawn when the user says "ingest this", "add this paper/article/book to the wiki", or drops a file into raw/.