Agent skill

Implement Improvements

by tobihagemann in tobihagemann/turbo

Validate improvements from .turbo/improvements.md, recommend a working set tailored to what's in the backlog, and run one lane: direct fixes, investigation, or planned work.

MITAuto-check: warningsBusiness, Finance & HR

Install Implement Improvements

The automated check flagged lines worth reading first. See the safety section below.

skills CLI
$ npx skills add tobihagemann/turbo --skill implement-improvements -a claude-code

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

GitHub CLI
$ gh skill install tobihagemann/turbo implement-improvements --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/tobihagemann/turbo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/codex/skills/implement-improvements .claude/skills/implement-improvements && 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
implement-improvements
GitHub stars
407
Token cost
~3.1k tokens
SKILL.md length
1,734 words
Files
4 (incl. references)
Skills in repo
81
Repo updated
First seen
Licence
MIT

At a glance

Validate improvements from .turbo/improvements.md, recommend a working set tailored to what's in the backlog, and run one lane: direct fixes, investigation, or planned work.

  • Works in 5 steps: Read the Backlog → Validate and Classify → Recommend, Confirm, and Update the Backlog → …
  • The user asks to implement improvements
  • SKILL.md covers Task Tracking, Step 1: Read the Backlog, Step 2: Validate and Classify and Step 3: Recommend, Confirm,…, plus 3 more sections
  • Calls git

What it does

Implement Improvements is an agent skill from tobihagemann/turbo. Validate improvements from .turbo/improvements.md, recommend a working set tailored to what's in the backlog, and run one lane: direct fixes, investigation, or planned work. One lane per session. Use when the user asks to "implement improvements", "work on improvements", "address improvements", "process improvement backlog", "tackle improvements", or "implement noted improvements".

Its SKILL.md is about 3.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including reference files (for example `references/direct-lane.md`, `references/investigate-lane.md` and `references/plan-lane.md`).

It sits in Business, Finance & HR, covering Operations and SOPs. It works with Git. The repository describes itself as: Reusable workflows for planning, building, reviewing, and shipping with Claude Code and Codex. The licence is MIT.

When your agent uses it

  • The user asks to implement improvements
  • Work on improvements
  • Address improvements
  • Process improvement backlog

Example prompts

  • “implement improvements”
  • “work on improvements”
  • “address improvements”
  • “/implement-improvements”

Workflow steps

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

  1. Read the Backlog
  2. Validate and Classify
  3. Recommend, Confirm, and Update the Backlog
  4. Run the Chosen Lane
  5. Prune Working-Set Entries from the Backlog

What it can do on your machine

Read from SKILL.md and the folder at commit 4b9f4cf. 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

    Shell commands in SKILL.md call:

    • git

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

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Implement Improvements loads about 3.1k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 102 tokens; SKILL.md has 1,734 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~102
When it runs · the whole SKILL.md, loaded when a task matches
~3.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.9k

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: warnings

The automated check found patterns that need a careful read before installing.

  • WarningTells the agent its actions are pre-authorized / not to stop for confirmationSKILL.md:67
    Pick the type without asking the user. Default to `plan` when a missing Type is genuinely ambiguous, and keep a recorded

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from tobihagemann/turbo at commit 4b9f4cf, republished under its MIT licence (© tobihagemann). 1,734 words, ~3,069 tokens.

Download SKILL.mdSave it as .claude/skills/implement-improvements/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
implement-improvements
description
Validate improvements from .turbo/improvements.md, recommend a working set tailored to what's in the backlog, and run one lane: direct fixes, investigation, or planned work. One lane per session. Use when the user asks to "implement improvements", "work on improvements", "address improvements", "process improvement backlog", "tackle improvements", or "implement noted improvements".

Implement Improvements

Validate improvements from .turbo/improvements.md, propose a specific working set based on the backlog's actual contents, and run one lane per session: direct, investigate, or plan. Mixing lanes in a single run tangles commits, so the skill processes exactly one lane each time. Entries outside the confirmed working set stay in the backlog for future runs.

Task Tracking

At the start, use update_plan to track each step, restating any remaining steps of a parent workflow alongside them:

  1. Read the backlog
  2. Validate and classify
  3. Recommend, confirm, and update the backlog
  4. Run the chosen lane
  5. Prune working-set entries from the backlog

Step 1: Read the Backlog

Read .turbo/improvements.md, relative to the repo root resolved with git rev-parse --show-toplevel, except inside a linked worktree — where git rev-parse --git-dir differs from --git-common-dir — in which case use the parent of the common dir. If the file does not exist, there are no improvements to implement; stop.

Parse all entries, extracting for each:

  • Summary (the ### heading)
  • Type (direct, investigate, or plan; may be missing in older entries — trivial and standard are accepted as legacy aliases for direct and plan)
  • Category
  • Where (file paths or areas)
  • Why (rationale)
  • Ceiling and Revisit (present when the entry records a deliberate simplification; Revisit alone when the entry waits on an outside event)
  • Noted (date)

Step 2: Validate and Classify

Improvements drift: files get renamed, code gets refactored, issues get fixed as side effects of other work. Before routing, validate each improvement and settle the Type of any entry whose Type is missing or wrong.

Validate

For each entry, verify whether the specific problem or opportunity described still exists. Do not rely on git log alone. Recent commits touching the same files do not mean the specific issue was addressed. Read the actual code and confirm:

  1. Files exist — Do the referenced files/paths still exist? When one was renamed or its code moved, validate the entry at the current location instead. This check marks the entry stale only when the code it names is gone.
  2. Problem persists — Read the relevant code sections. Is the exact issue or opportunity described in the entry still present? Check the specific claims: if the entry says a function is uncalled, verify it has no callers; if it says error handling is missing, check whether it was added.
  3. Revisit condition met — For an entry carrying a Revisit field, check whether the recorded condition now holds. A shipped simplification is present by construction, so its presence alone says nothing about whether the fuller version is worth building yet.
  4. Stated scope matches the real gap — For an entry claiming missing coverage, read what existing tests already pin before accepting its scope: a test that substitutes a test double at a boundary pins the behavior on one side of it and leaves the boundary itself unpinned, so a request to cover several variants often reduces to the single boundary they share. Before dropping an item on the grounds that an existing check covers it, confirm that the check pins that item through its own inputs or match patterns rather than inferring it from the check's name or description; an item no existing check pins stays in the entry's scope. Restate such an entry at its real scope, classify it Active, and use the restatement as its summary in Step 3.
  5. Claimed consequence holds — For an entry claiming that two paths behave differently, that a change would alter observable behavior, or that the code as it stands leads to a stated outcome, verify the consequence itself rather than confirming only that the code it points at exists. For a claimed difference, between two paths or between the behavior before and after a change, read what each actually returns, exercising both when reading cannot settle it. For a claimed outcome, follow the path from the named code to that outcome and confirm nothing later on that path already stops it. When the claim is that nothing but the case it names reaches or relies on the named code, read that code's own tests: they surface dependents an entry written from a single path routinely omits, and turning up none leaves the claim unproven. When the named code is present but its stated consequence is false, restate the entry at the benefit it actually delivers, classify it Active, and use the restatement as its summary in Step 3; classify it Stale when no benefit survives.

Before using a restatement as an entry's summary in Step 3, confirm each fact it adds to the entry against the code, or against the dependency's shipped artifact when the fact concerns a dependency.

Classify each entry as:

  • Active — The described problem or opportunity is confirmed present in the current code
  • Deferred — The entry carries a Revisit condition that does not yet hold: the shipped approach remains the right one, or the event the entry waits on has not happened
  • Stale — The code the entry names no longer exists, the specific issue has been resolved, or the entry's premise never held (cite evidence: what changed and where, or why the claim is false)
  • Unclear — Cannot determine from code alone, needs user input

When in doubt, classify as Active. The cost of re-examining a resolved issue is low; dismissing a valid improvement is high.

Classify or Correct the Type

For any Active entry without a Type field, infer one on the fly. For an Active entry whose Type the code read contradicts, correct it. Base the classification on the code you just read during validation, not just the entry's one-line summary.

  • direct — Clear scope and a known approach, ready to apply via $implement.
  • investigate — A symptom that needs root-cause analysis first: unclear root cause, performance question, intermittent bug, "something feels off".
  • plan — Everything else: the approach warrants writing down before implementing (multi-file refactor, test additions, feature work). Dispatched to $turboplan, which routes the work itself.

Pick the type without asking the user. Default to plan when a missing Type is genuinely ambiguous, and keep a recorded Type the code read does not contradict.

Step 3: Recommend, Confirm, and Update the Backlog

Output the backlog status as text first, grouped by type and status. Include each entry's category inline and a category tally across active entries:

## Improvement Backlog Status

### Active (N)
Categories: refactor (N), performance (N), testing (N), docs (N)

**Direct (N)**
- [summary] (category) — [one-line reason it's still relevant]

**Investigate (N)**
- [summary] (category) — [one-line reason it's still relevant]

**Plan (N)**
- [summary] (category) — [one-line reason it's still relevant]

### Deferred (N)
- [summary] — [the revisit condition, and what still has to happen]

### Stale (N)
- [summary] — [one-line reason it's stale]

### Unclear (N)
- [summary] — [what's ambiguous]
Show full SKILL.md (687 more words)Show less
Recommend a Working Set

When no entry is Active, skip the recommendation: a Deferred entry is not a candidate.

Pick one specific working set tailored to the active entries. Read the entries again before recommending and weigh:

  • Cohesion — Entries that share files, modules, or themes are stronger when batched. A cluster of related testing or reliability entries usually beats a scattered mix.
  • Decisiveness — One investigation that unblocks several deferred entries can outweigh a larger direct batch.
  • Impact vs effort — A reliability or correctness entry often outweighs lower-stakes cleanups even when it's a single entry.
  • Lane shape — Each lane batches a cluster, just in different shapes. Direct groups clear-scope fixes into one $implement run. Investigate dispatches $investigate per symptom, then shares one $implement for the concluded fixes. Plan hands a cohesive cluster to $turboplan, which routes it to a plan file.
  • Unit of work size — Right-size the session. Prefer the whole cohesive cluster over a narrow filter unless the filter clearly preserves a coherent unit of work; picking 1–2 entries off a cluster of 7 wastes the slot. Route any entry that turns out to be a clear-scope direct fix to the direct lane instead.
  • Backlog state — Heavy direct concentration calls for clearing the cluster; a long-deferred symptom often deserves the slot.

State the recommendation as: lane + concrete working set (specific entries or a category-scoped subset) + one or two sentences on why this beats the alternatives. Then list 1–3 honest alternatives, each named with the actual entry or subset (e.g., "investigate the flaky presence test", "plan lane on persist-before-send"). When only one lane has active entries, recommend that lane and skip alternatives.

Confirm with the User

Use request_user_input to confirm. Combine into the same prompt:

  1. Confirm the recommended working set or pick one of the named alternatives — include only when active entries exist
  2. Whether to remove stale entries — include only when stale entries exist
  3. Resolution for unclear items — include only when unclear entries exist

Skip the call when no item applies.

If the user confirmed stale removal, edit .turbo/improvements.md to delete the stale entries.

Rewrite in .turbo/improvements.md each Active or Deferred entry whose path, scope, count, consequence, or Type Step 2 corrected, changing only the fields the correction touches. When that changes an entry's summary, update each Paired with line in its counterpart entries that names the old title.

Compute the working set from the confirmed choice. If the working set is empty, stop.

Step 4: Run the Chosen Lane

Read the reference file for the confirmed lane and follow its phases:

State the chosen lane before continuing with the reference file.

Step 5: Prune Working-Set Entries from the Backlog

Edit .turbo/improvements.md to delete the working-set entries that the lane processed. "Processed" means:

  • Direct lane — entries whose fixes were applied
  • Investigate lane — entries the applied fixes resolve in full
  • Plan lane — entries now captured in the plan produced by $turboplan; treat them as processed once the plan is written.

Keep any entries the lane re-classified mid-flight (direct → investigate/plan, or investigate → plan). These stay in the backlog for a future run. Delete the file if no entries remain.

Rewrite in place each entry the investigate lane investigated that stays in the backlog: restate its summary and Where as what remains to do, put what the investigation established in its Why (the root cause it confirmed, or the hypotheses it refuted when the cause stayed unresolved), and set the Type the remainder calls for. When the entry waits on an outside event, such as an upstream fix, record that event as its Revisit. When the rewrite changes the summary, update each Paired with line in counterpart entries that names the old title.

When a processed entry carries a Paired with line, drop that reference from each counterpart entry it names, so no backlog is left pointing at an entry that no longer exists.

Rules

  • .turbo/ is gitignored. Edits to .turbo/improvements.md are local-only and do not need to be staged or committed.
  • Run exactly one lane per session. Leave other active entries in the backlog for a future run.

© tobihagemann, 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 3 other files (references) in codex/skills/implement-improvements of tobihagemann/turbo.

  • SKILL.md
  • references/direct-lane.md
  • references/investigate-lane.md
  • references/plan-lane.md

Open the folder on GitHubat commit 4b9f4cf

Compare with similar skills

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Works with

Questions about Implement Improvements

What does Implement Improvements do?

Validate improvements from .turbo/improvements.md, recommend a working set tailored to what's in the backlog, and run one lane: direct fixes, investigation, or planned work. Implement Improvements is an agent skill from tobihagemann/turbo.md, recommend a working set tailored to what's in the backlog, and run one lane: direct fixes, investigation, or planned work.

When should I use Implement Improvements?

Implement Improvements fits situations like: the user asks to implement improvements; work on improvements; address improvements; process improvement backlog.

How do I install Implement Improvements in Claude Code?

Run `npx skills add tobihagemann/turbo --skill implement-improvements -a claude-code`. Or copy the skill folder (codex/skills/implement-improvements in tobihagemann/turbo) into .claude/skills/implement-improvements in your project. Claude Code loads it when a task matches its description.

How do I install Implement Improvements in Codex?

Run `npx skills add tobihagemann/turbo --skill implement-improvements -a codex`. Or copy the skill folder (codex/skills/implement-improvements in tobihagemann/turbo) into .agents/skills/implement-improvements in your project. Codex loads it when a task matches its description.

Can I use Implement Improvements 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 tobihagemann/turbo --skill implement-improvements -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/implement-improvements, .gemini/skills/implement-improvements, .github/skills/implement-improvements and .opencode/skills/implement-improvements in your project.

What does Implement Improvements need to run?

Going by SKILL.md and its folder, Implement Improvements needs the command-line tools its instructions call (git).

Does Implement Improvements access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Implement Improvements safe to install?

Our automated static check of SKILL.md flagged 1 warning(s): tells the agent its actions are pre-authorized / not to stop for confirmation. Read the flagged lines before installing; the check is not a guarantee either way.

What licence does Implement Improvements use?

Implement Improvements 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 Implement Improvements use?

About 3.1k tokens (SKILL.md is roughly 12k 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 834 tokens, read only when the agent opens those files.

What are the alternatives to Implement Improvements?

Skills that share tags, products or a category with Implement Improvements: Oceanbase Source Analysis (oceanbase/obdiag, 163 stars), Agentsop Aider (agentsope/SkillAlchemy, 459 stars), Aboutsecurity Content Ingestion (wgpsec/AboutSecurity, 1.8k stars) and Handover (k1ein-chen/Harness-Starter, 119 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Implement Improvements?

tobihagemann (a GitHub user) maintains it in tobihagemann/turbo, which has 407 GitHub stars. The repository holds 81 skills in this directory. The repository was last updated on October 7, 2026.

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