Agent skill

Tc Tracker

by alirezarezvani in alirezarezvani/claude-skills

A skill your agent uses when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions.

MITAuto-check passedAgent Workflows

Install Tc Tracker

skills CLI
$ npx skills add alirezarezvani/claude-skills --skill tc-tracker -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install alirezarezvani/claude-skills tc-tracker --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/alirezarezvani/claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/engineering/skills/tc-tracker .claude/skills/tc-tracker && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
tc-tracker
GitHub stars
28k
Token cost
~2.6k tokens
SKILL.md length
1,022 words
Files
10 (incl. scripts, references)
Skills in repo
342
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions.

  • Works in 5 steps: Initialize tracking in a project → Create a new TC record → Update a TC record → …
  • The user asks to track technical changes
  • SKILL.md covers Overview, Storage Layout, TC ID Convention and State Machine, plus 9 more sections
  • Runs Python scripts from its folder; calls python3

What it does

Tc Tracker is an agent skill from alirezarezvani/claude-skills. 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.

Its SKILL.md is about 2.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 11 other files, including scripts and reference files (for example `README.md`, `references/handoff-format.md` and `references/lifecycle.md`).

It sits in Agent Workflows, covering Session handoff. The repository describes itself as: 380 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 380+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8… The licence is MIT.

When your agent uses it

  • The user asks to track technical changes
  • Create change records
  • Manage TC lifecycles
  • Hand off work between AI sessions

Example prompts

  • “/tc-tracker”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Initialize tracking in a project
  2. Create a new TC record
  3. Update a TC record
  4. View status
  5. Validate a record or registry

What it can do on your machine

Read from SKILL.md and the folder at commit 19392f7. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 5 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Tc Tracker loads about 2.6k tokens when it runs, and up to ~6.2k if it reads all its reference files. Until then it costs about 62 tokens; SKILL.md has 1,022 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~2.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~6.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from alirezarezvani/claude-skills at commit 19392f7, republished under its MIT licence (© alirezarezvani). 1,022 words, ~2,557 tokens.

Download SKILL.mdSave it as .claude/skills/tc-tracker/SKILL.md (or your agent's skills folder). This skill also uses 9 other files; get the full folder from GitHub.
name
tc-tracker
description
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.

TC Tracker

Track every code change with structured JSON records, an enforced state machine, and a session handoff format that lets a new AI session resume work cleanly when a previous one expires.

Overview

A Technical Change (TC) is a structured record that captures what changed, why it changed, who changed it, when it changed, how it was tested, and where work stands for the next session. Records live as JSON in docs/TC/ inside the target project, validated against a strict schema and a state machine.

Use this skill when the user:

  • Asks to "track this change" or wants an audit trail for code modifications
  • Wants to hand off in-progress work to a future AI session
  • Needs structured release notes that go beyond commit messages
  • Onboards an existing project and wants retroactive change documentation
  • Asks for /tc init, /tc create, /tc update, /tc status, /tc resume, or /tc close

Do NOT use this skill when:

  • The user only wants a changelog from git history (use engineering/changelog-generator)
  • The user only wants to track tech debt items (use engineering/tech-debt-tracker)
  • The change is trivial (typo, formatting) and won't affect behavior

Storage Layout

Each project stores TCs at {project_root}/docs/TC/:

docs/TC/
├── tc_config.json          # Project settings
├── tc_registry.json        # Master index + statistics
├── records/
│   └── TC-001-04-05-26-user-auth/
│       └── tc_record.json  # Source of truth
└── evidence/
    └── TC-001/             # Log snippets, command output, screenshots

TC ID Convention

  • Parent TC: TC-NNN-MM-DD-YY-functionality-slug (e.g., TC-001-04-05-26-user-authentication)
  • Sub-TC: TC-NNN.A or TC-NNN.A.1 (letter = revision, digit = sub-revision)
  • NNN is sequential, MM-DD-YY is the creation date, slug is kebab-case.

State Machine

planned -> in_progress -> implemented -> tested -> deployed
   |            |              |           |          |
   +-> blocked -+              +- in_progress <-------+
        |                          (rework / hotfix)
        +-> planned

See references/lifecycle.md for the full transition table and recovery flows.

Workflow Commands

The skill ships five Python scripts that perform deterministic, stdlib-only operations on TC records. Each one supports --help and --json.

1. Initialize tracking in a project
bash
python3 scripts/tc_init.py --project "My Project" --root .

Creates docs/TC/, docs/TC/records/, docs/TC/evidence/, tc_config.json, and tc_registry.json. Idempotent — re-running reports "already initialized" with current stats.

2. Create a new TC record
bash
python3 scripts/tc_create.py \
  --root . \
  --name "user-authentication" \
  --title "Add JWT-based user authentication" \
  --scope feature \
  --priority high \
  --summary "Adds JWT login + middleware" \
  --motivation "Required for protected endpoints"

Generates the next sequential TC ID, creates the record directory, writes a fully populated tc_record.json (status planned, R1 creation revision), and updates the registry.

3. Update a TC record
bash
# Status transition (validated against the state machine)
python3 scripts/tc_update.py --root . --tc-id TC-001-04-05-26-user-auth \
  --set-status in_progress --reason "Starting implementation"

# Add a file
python3 scripts/tc_update.py --root . --tc-id TC-001-04-05-26-user-auth \
  --add-file src/auth.py:created

# Append handoff data
python3 scripts/tc_update.py --root . --tc-id TC-001-04-05-26-user-auth \
  --handoff-progress "JWT middleware wired up" \
  --handoff-next "Write integration tests" \
  --handoff-next "Update README"

Every change appends a sequential R<n> revision entry, refreshes updated, and re-validates against the schema before writing atomically (.tmp then rename).

4. View status
bash
# Single TC
python3 scripts/tc_status.py --root . --tc-id TC-001-04-05-26-user-auth

# All TCs (registry summary)
python3 scripts/tc_status.py --root . --all --json
5. Validate a record or registry
bash
python3 scripts/tc_validator.py --record docs/TC/records/TC-001-.../tc_record.json
python3 scripts/tc_validator.py --registry docs/TC/tc_registry.json

Validator enforces the schema, checks state-machine legality, verifies sequential R<n> and T<n> IDs, and asserts approval consistency (approved=true requires approved_by and approved_date).

See references/tc-schema.md for the full schema.

Slash-Command Dispatcher

The repo ships a /tc slash command at commands/tc.md that dispatches to these scripts based on subcommand:

CommandAction
/tc initRun tc_init.py for the current project
/tc create <name>Prompt for fields, run tc_create.py
/tc update <tc-id>Apply user-described changes via tc_update.py
/tc status [tc-id]Run tc_status.py
/tc resume <tc-id>Display handoff, archive prior session, start a new one
/tc close <tc-id>Transition to deployed, set approval
/tc exportRe-render all derived artifacts
/tc dashboardRe-render the registry summary

The slash command is the user interface; the Python scripts are the engine.

Session Handoff Format

The handoff block lives at session_context.handoff inside each TC and is the single most important field for AI continuity. It contains:

  • progress_summary — what has been done
  • next_steps — ordered list of remaining actions
  • blockers — anything preventing progress
  • key_context — critical decisions, gotchas, patterns the next bot must know
  • files_in_progress — files being edited and their state (editing, needs_review, partially_done, ready)
  • decisions_made — architectural decisions with rationale and timestamp

See references/handoff-format.md for the full structure and fill-out rules.

Validation Rules (Always Enforced)

  1. State machine — only valid transitions are allowed.
  2. Sequential IDs — revision_history uses R1, R2, R3...; test_cases uses T1, T2, T3....
  3. Append-only history — revision entries are never modified or deleted.
  4. Approval consistency — approved=true requires approved_by and approved_date.
  5. TC ID format — must match TC-NNN-MM-DD-YY-slug.
  6. Sub-TC ID format — must match TC-NNN.A or TC-NNN.A.N.
  7. Atomic writes — JSON is written to .tmp then renamed.
  8. Registry stats — recomputed on every registry write.
Show full SKILL.md (404 more words)Show less

Non-Blocking Bookkeeping Pattern

TC tracking must NOT interrupt the main workflow.

  • Never stop to update TC records inline. Keep coding.
  • At natural milestones, spawn a background subagent to update the record.
  • Surface questions only when genuinely needed ("This work doesn't match any active TC — create one?"), and ask once per session, not per file.
  • At session end, write a final handoff block before closing.

Retroactive Bulk Creation

For onboarding an existing project with undocumented history, build a retro_changelog.json (one entry per logical change) and feed it to tc_create.py in a loop, or extend the script for batch mode. Group commits by feature, not by file.

Anti-Patterns

Anti-patternWhy it's badDo this instead
Editing revision_history to "fix" a typoHistory is append-only — tampering destroys the audit trailAdd a new revision that corrects the field
Skipping the state machine ("just set status to deployed")Bypasses validation and hides skipped phasesWalk through in_progress -> implemented -> tested -> deployed
Creating one TC per file changedFragments related work and explodes the registryOne TC per logical unit (feature, fix, refactor)
Updating TC inline between every code editSlows the main agent, wastes contextSpawn a background subagent at milestones
Marking approved=true without approved_byValidator will reject; misleading audit trailAlways set approved_by and approved_date together
Overwriting tc_record.json directly with a text editorRisks corruption mid-write and skips validationUse tc_update.py (atomic write + schema check)
Putting secrets in notes or evidenceRecords are committed to the repoReference an env var or external secret store
Reusing TC IDs after deletionBreaks the sequential guarantee and confuses historyIncrement forward only — never recycle
Letting next_steps go staleDefeats the purpose of handoffUpdate on every milestone, even if it's "nothing changed"

Cross-References

  • engineering/changelog-generator — Generates Keep-a-Changelog release notes from Conventional Commits. Pair it with TC tracker: TC for the granular per-change audit trail, changelog for user-facing release notes.
  • engineering/tech-debt-tracker — For tracking long-lived debt items rather than discrete code changes.
  • engineering/focused-fix — When a bug fix needs systematic feature-wide repair, run /focused-fix first then capture the result as a TC.
  • project-management/decision-log — Architectural decisions made inside a TC's decisions_made block can also be promoted to a project-wide decision log.
  • engineering-team/code-reviewer — Pre-merge review fits naturally into the tested -> deployed transition; capture the reviewer in approval.approved_by.

References in This Skill

© alirezarezvani, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 9 other files (scripts, references) in engineering/skills/tc-tracker of alirezarezvani/claude-skills.

  • SKILL.md
  • README.md
  • references/handoff-format.md
  • references/lifecycle.md
  • references/tc-schema.md
  • scripts/tc_create.py
  • scripts/tc_init.py
  • scripts/tc_status.py
  • scripts/tc_update.py
  • scripts/tc_validator.py

Open the folder on GitHubat commit 19392f7

Compare with similar skills

Tc Tracker next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Tc Tracker compared with similar skills
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Questions about Tc Tracker

What does Tc Tracker do?

A skill your agent uses when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions. Tc Tracker is an agent skill from alirezarezvani/claude-skills. Use when the user asks to track technical changes, create change records, manage TC lifecycles, or hand off work between AI sessions.

When should I use Tc Tracker?

Tc Tracker fits situations like: the user asks to track technical changes; create change records; manage TC lifecycles; hand off work between AI sessions.

How do I install Tc Tracker in Claude Code?

Run `npx skills add alirezarezvani/claude-skills --skill tc-tracker -a claude-code`. Or copy the skill folder (engineering/skills/tc-tracker in alirezarezvani/claude-skills) into .claude/skills/tc-tracker in your project. Claude Code loads it when a task matches its description.

How do I install Tc Tracker in Codex?

Run `npx skills add alirezarezvani/claude-skills --skill tc-tracker -a codex`. Or copy the skill folder (engineering/skills/tc-tracker in alirezarezvani/claude-skills) into .agents/skills/tc-tracker in your project. Codex loads it when a task matches its description.

Can I use Tc Tracker in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add alirezarezvani/claude-skills --skill tc-tracker -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tc-tracker, .gemini/skills/tc-tracker, .github/skills/tc-tracker and .opencode/skills/tc-tracker in your project.

What does Tc Tracker need to run?

Going by SKILL.md and its folder, Tc Tracker needs Python for the scripts in its folder and the command-line tools its instructions call (python3). Our summary lists: Python 3.

Does Tc Tracker access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Tc Tracker safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Tc Tracker use?

Tc Tracker is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tc Tracker use?

About 2.6k tokens (SKILL.md is roughly 10k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 3.7k tokens, read only when the agent opens those files.

What are the alternatives to Tc Tracker?

Skills that share tags, products or a category with Tc Tracker: Orca CLI (stablyai/orca, 87k stars), Beads Task Memory (gastownhall/beads, 28k stars), Codemap (JordanCoin/codemap, 704 stars) and Agent Manager Fleet TUI (YoanWai/agent-manager, 576 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tc Tracker?

alirezarezvani (a GitHub user) maintains it in alirezarezvani/claude-skills, which has 27,829 GitHub stars. The repository holds 342 skills in this directory. The repository was last updated on August 30, 2026.

Source: alirezarezvani/claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.