Agent skill

Tlc Spec Lean

by tech-leads-club in tech-leads-club/agent-skills

Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build…

CC-BY-4.0Auto-check passedAgent Workflows

Install Tlc Spec Lean

skills CLI
$ npx skills add tech-leads-club/agent-skills --skill tlc-spec-lean -a claude-code

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

GitHub CLI
$ gh skill install tech-leads-club/agent-skills tlc-spec-lean --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/tech-leads-club/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/'packages/skills-catalog/skills/(development)/tlc-spec-lean' .claude/skills/tlc-spec-lean && 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
tlc-spec-lean
GitHub stars
7k
Token cost
~5.1k tokens
SKILL.md length
2,929 words
Files
15 (incl. scripts, references)
Skills in repo
74
Repo updated
First seen
Licence
CC-BY-4.0

At a glance

Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build…

  • Works in 8 steps: Every check is one observable claim with… → Tests assert what the checks say, never… → Never weaken an assertion, delete a… → …
  • The user says tlc-spec-lean
  • SKILL.md covers Why this shape, Critical rules, Profile and Artifacts, plus 8 more sections
  • Runs Python scripts from its folder; calls python3 and git

What it does

Tlc Spec Lean is an agent skill from tech-leads-club/agent-skills. Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build, then an independent Verifier. Use when the user says "tlc-spec-lean", "plan feature", "specify feature", "write the checks", "build this plan", or "verify work". Do NOT use for standalone design documents unattached to a feature, architecture decomposition analysis, or work that already has a task list or checklist to…

Its SKILL.md is about 5.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 17 other files, including scripts and reference files (for example `references/build.md`, `references/checks.md` and `references/memory.md`).

It sits in Agent Workflows, covering Spec-driven development and Task breakdown. The repository describes itself as: The secure, validated skill registry for professional AI coding agents. Extend Antigravity, Claude Code, Cursor, Copilot and more with absolute confidence. The licence is CC-BY-4.0.

When your agent uses it

  • The user says tlc-spec-lean
  • Specify feature
  • Write the checks
  • Build this plan

Example prompts

  • “tlc-spec-lean”
  • “plan feature”
  • “specify feature”
  • “/tlc-spec-lean”

Requirements

  • Python 3

Workflow steps

8 steps, taken from the first numbered list in SKILL.md.

  1. Every check is one observable claim with a concrete value plus the proof - the test
  2. Tests assert what the checks say, never what the code happens to do. Never write a test by
  3. Never weaken an assertion, delete a test, or skip one to make a suite pass. A genuinely
  4. Checks and Test policy rows are fixed once approved. In the design, Landing, Relations
  5. The Verifier is a fresh sub-agent, never the author, never optional, never waiting to
  6. The profile is a floor and it is not a secret. The verification report names it, or "no
  7. The completion gate is a script, not a feeling: validate_verification.py must exit 0.
  8. Blast radius: an approved spec authorizes local edits and local commits. git push,

What it can do on your machine

Read from SKILL.md and the folder at commit 6df68d5. 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 9 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3
    • 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

Tlc Spec Lean loads about 5.1k tokens when it runs, and up to ~25k if it reads all its reference files. Until then it costs about 135 tokens; SKILL.md has 2,929 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~135
When it runs · the whole SKILL.md, loaded when a task matches
~5.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~25k

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 tech-leads-club/agent-skills at commit 6df68d5, republished under its CC-BY-4.0 licence (© tech-leads-club). 2,929 words, ~5,066 tokens.

Download SKILL.mdSave it as .claude/skills/tlc-spec-lean/SKILL.md (or your agent's skills folder). This skill also uses 14 other files; get the full folder from GitHub.
name
tlc-spec-lean
description
Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build, then an independent Verifier. Use when the user says "tlc-spec-lean", "plan feature", "specify feature", "write the checks", "build this plan", or "verify work". Do NOT use for standalone design documents unattached to a feature, architecture decomposition analysis, or work that already has a task list or checklist to execute.
license
CC-BY-4.0
metadata.author
Tech Leads Club - github.com/tech-leads-club
metadata.version
1.1.0

Tech Lead's Club - Spec, Lean

Freeze the obligations. Free the plan. Prove it with someone who did not build it. Derived from tlc-spec-driven 3.3.0 (Felipe Rodrigues), tlc-plan, and tlc-implement.

┌──────┐   ┌────────┐   ┌───────┐   ┌────────┐
│ PLAN │ → │ CHECKS │ → │ BUILD │ → │ VERIFY │
└──────┘   └────────┘   └───────┘   └────────┘
 read it    obligations   yours       always

Four moves, two artifacts before code, one after. A human confirms what must be true and how it is being built in one document, and only then does any of it become an obligation with a proof attached. There is no task breakdown, and the plan carries no component catalogue: what is hard to reverse gets a one-way door with its literal shape, and everything reversible is decided while building and reviewed in the diff.

Why this shape

The dominant failure of a coding agent is not bad reasoning, it is a requirement that was read and never became an active obligation - and then a completion claim on top of it. The mitigation that measures well is a small, frozen, external obligation set plus a verifier that is not the author; a self-check reproduces the author's own blind spot. So this skill spends its budget on those two things and refuses to spend it on choreographing how the model works.

Two consequences worth stating up front, because they are what make this different from a conventional spec-driven flow:

  • Granularity is not quality. Splitting a feature into fifteen one-file tasks buys ordering, not correctness, and it costs a re-read of the process on every task. Proof coverage buys correctness.
  • A plan the model must obey competes with the obligations for attention. Fields like Where, Tools, Depends on are the model's job to decide, so they are not written down.

Critical rules

The pinned set. These hold even if no reference file is read, and they are the only rules that never scale down with the profile.

  1. Every check is one observable claim with a concrete value plus the proof - the test or command whose exit code settles it. No proof, no check.
  2. Tests assert what the checks say, never what the code happens to do. Never write a test by reading the implementation.
  3. Never weaken an assertion, delete a test, or skip one to make a suite pass. A genuinely wrong check is a stop-and-ask, not an edit.
  4. Checks and Test policy rows are fixed once approved. In the design, Landing, Relations and Surface are additive - a door discovered while building gets a row before the code that closes it, and a row the user approved is never rewritten. Flow and Impact are neither: they are kept true, so a different path changes the hop in that path's commit.
  5. The Verifier is a fresh sub-agent, never the author, never optional, never waiting to be asked. Whoever holds the whole feature dispatches it after the last commit of the feature lands - over <feature base>..HEAD, with every check. Never by a builder, and never as a child of one. A builder finishes, reports, and stops. The work is not done at the last commit; it is done when the Verifier's report accounts for every check.
  6. The profile is a floor and it is not a secret. The verification report names it, or "no faults injected" reads exactly like forgetting to inject them.
  7. The completion gate is a script, not a feeling: validate_verification.py must exit 0.
  8. Blast radius: an approved spec authorizes local edits and local commits. git push, deploy, and production data changes need an explicit go-ahead for that action.

Profile

The project declares how much runs, in AGENTS.md or equivalent. Absent a declaration: light. Same three levels as tlc-implement, gated the same way, so moving between the two skills needs no second vocabulary.

markdown
## tlc-spec-lean

profile: light
budget: 150k
ProfileAddsCannot catch
light (default)proofs run at HEAD with each named test shown to exist and run, one located assertion per check, level and sampling gaps, Swept existing re-reada set member with no proof; a test that would pass under a wrong implementation
standardthe Coverage join recomputed, Test policy rows with a verdict each, one fault per assertion surfacea check that contradicts a binding source; a screen nobody built
uibinding sources opened and compared, per-screen enumeration of copy and arrangementonly spacing, colour and type weight, enumerated per screen

Each step adds a class of failure detected, so a cheap profile is not a discount on the same product - read the right column before choosing it. Two things about light are worth saying out loud, because its own row says them and they are easy to skim past: it will not notice an enumerated set member that nobody proved, and it will not notice a test that passes under a wrong implementation. standard exists for exactly those two.

ui costs nothing on work with no interface: every screen step is conditional on a screen existing. A step whose input is empty costs a line, not a pass ("no set rows", "no binding source").

The Coverage join is written into checks.md at every profile - the join is what makes an omission structural, and that costs nothing at authoring time. What standard buys is the Verifier recomputing it from the authority over each set instead of reading the author's table back.

The profile is a pin, not a preference, and unlike tlc-implement that is enforced rather than asked for: validate_verification.py fails a report whose profile differs from the one checks.md was approved under, and fails a standard report with no fault rows or no recomputed coverage, and a ui report with no binding-sources section. So a step that did not run stays distinguishable from a step that was forgotten, which is the whole reason to declare a floor.

Where the profile looks too thin for the feature in hand, say so in one line and let the user raise it. Doing more than the profile in silence costs the predictability that made declaring it worthwhile.

Artifacts

.specs/
├── STATE.md                    # Decisions log (AD-NNN) + Handoff snapshot
├── LESSONS.md                  # rendered by scripts/lessons.py - never hand-edit
├── lessons.json                # machine-owned
└── features/<feature>/
    ├── plan.md                 # problem, flow, impact, then the rest of the shape, then criteria; audit last
    ├── checks.md               # claims + proofs, the coverage join, test policy, swept
    └── verification.md         # the Verifier's report

Create each file when its phase produces content. For a change under roughly three files with no one-way door, write only checks.md with an ## Intent paragraph and skip plan.md - one bounded escape, not a sizing matrix.

Understanding and obligations are separate artifacts

plan.md exists because a human has to be able to plan and object before anything turns into a claim with a test selector attached. Reading forty checks to reconstruct what is being built is not planning, and writing the checks in the same pass that decides the shape produces checks that ratify whatever was already assumed.

Both halves live in one file because they are one review. The file boundary is the semantic one: on this side, what a human confirms; on the other, obligations with proofs. Splitting the plan into a spec and a design would cut it in a place that matches neither, and would buy two mandatory stops for one feature. File order is for reading - Problem, Flow, Impact, then the rest of the shape, then the criteria, then the audit tables. Writing order is not: write the problem, walk the surfaces, write the criteria, then fill the shape. That is what stops a criterion from being invented to justify a component. The closure gate still requires every criterion to land somewhere in Flow, Relations or Surface, or it is out of scope or a gap in the shape.

The derivation into checks.md is the load-bearing part, not paperwork. Every route in Surface owes a Coverage set row whose members are its statuses; every door in Landing owes a check; every entity in Relations owes one. A shape section with nothing pointing back at it from checks.md is either dead or unproven, and validate_checks.py warns on the common case.

The design half exists; the component catalogue does not. What made design documents rot was never the diagram, it was Purpose / Location / Interfaces / Dependencies per class - reversible detail that goes stale within weeks and then misleads the next reader with the authority of a written document. None of those fields exists here. Five bounded sections:

SectionReviewsKept out
Flowthe path, one line per hopany module that neither exists nor is created by a door - that is placement
Impactwhat changes underneath: terms, and existing datarisk registers
Relationsentities, cardinality, one-way constraintscolumns and types
Surfaceroute, in, out, statusesrequest-body specification, and check ids - those do not exist yet
Landingthe one-way doors, with the literal shape and the rejected alternativeanything a refactor reverses

Which folder, how many classes, what the private method is called: the diff. Reversible, answered by the repo's conventions, and never worth an artifact. That is the deliberate trade, and it is the only one.

A bet still open when you get here - two architectures with live alternatives, each needing to be costed against this repository - does not fit in a Landing row, and a row is the only shape this artifact has for it. Whatever the project uses to settle one (an ADR, an RFC, a spike) comes first; then the plan records the shape that won and makes it reviewable.

Flow

Plan - the problem, then the path and what the change disturbs, then the rest of the shape, then the criteria. Writing still goes problem → surfaces → criteria → shape. Facts you look up; decisions you ask - and when you ask, concrete options with your recommendation, at most two per turn. Two enumerations do the finding, because "consider the edge cases" finds nothing: the surfaces this feature exposes, each carrying the same decisions every time it appears, and the nine implicit-requirement dimensions. Both take a mandatory n/a - <reason>, so a blank is an item nobody decided rather than one that does not apply. One artifact a human reads and objects to before any check exists. Full process, how to ask, rules per shape section, template and closure gate: plan.md.

Checks - derive claims with proofs from the plan, join every enumerated set member to a check, and record where each swept dimension landed. Close with ## Handoff and the arithmetic; if the estimate exceeds the budget, stop for the mechanism ask before Build. This is the artifact everything downstream refers to by check number: checks.md.

Build - your call how, after the ## Handoff arithmetic and, if the estimate exceeds the budget, the user's mechanism choice. Write the tests from the checks, implement, run each proof, commit in coherent pieces. No task list, no per-task review tables. Boundaries, Landing timing, handoff and the scope guardrail: build.md.

Verify - when the last commit of the feature lands, dispatch a fresh Verifier in the same turn. Do not ask. Do not wait for "verify work". Procedure, report format and scoped re-verification: verify.md.

Durable memory - project decisions, session handoff, and the lessons layer: memory.md.

Show full SKILL.md (1,152 more words)Show less

Scripts

Resolve <skill-dir> as the directory containing this SKILL.md and invoke python3 <skill-dir>/scripts/<name>.py. Project data under .specs/ stays relative to the project root; pass --root when cwd differs. A non-zero exit means STOP and fix.

WhenCommand
Before presenting the planvalidate_plan.py <feature>
Before starting to buildvalidate_checks.py <feature>
Before each commitcheck_commit.py --message "<msg>"
Before declaring donevalidate_verification.py <feature>
At distillationlessons.py add ...
After editing a validator or templateselftest.py

validate_plan.py runs the closure gate and guards the shape half against becoming what it replaced: it fails a criterion with no SHALL, an assumption with no chosen default, an Observable row whose landing is blank or whose n/a carries no reason, a Landing row with no literal shape or no rejected alternative, columns and types inside Relations, a Surface route with no statuses, and any section left blank rather than answered with None - <why>. validate_checks.py is the omission catcher: it fails a check with no proof, a coverage row whose declared size exceeds the members actually assigned, a missing swept dimension, and a missing profile line, and warns on a route the plan reviewed that no check mentions. validate_verification.py fails a PASS report that cites no file:line, records a surviving mutant, leaves an Unproven member, or was written by the author.

Skip a script only when no code-execution tool exists; then perform the same checks by reading the artifact and say once in chat that you are in the degraded path.

selftest.py applies this skill's own discipline to its gates: it mutates a filled-in fixture set once per rule and requires every mutant to be killed, runs negative controls proving a profile-scoped gate does not fire below its profile, and smoke-runs every script shipped here - an unexercised script is where a crash hides, and the completion gate once exited 0 with nothing gated. Run it after editing a validator or a template - a validator that exits 0 on everything is decoration, one that exits 1 on everything makes light unusable, and only injection tells the two apart. The fixtures in scripts/fixtures/ are also a complete worked example of a passing standard artifact set.

Sub-agents and handoff

One builder unless the estimate does not fit. Pack whole slices - never split a slice - accumulating while the running estimate stays under the declared budget (default 150k tokens, from wc -c on the files each slice touches, divided by four). Prefer a cut where the surface changes. Write the intended split into checks.md under ## Handoff with the arithmetic, after the checks exist and before any code: a number with its reason can be argued with, a bare number can only be trusted.

Then the gate, and only then:

  • The estimate fits → one builder. Do not ask. Do not offer a spawn.
  • The estimate exceeds the budget → stop. Do not start the implementation. Ask which mechanism to use, with both exits named:
    • handoff — cut at the surface boundary already written, batches sequential and only on green
    • one builder — stay, and accept compaction / context loss
  • A slice that alone exceeds the budget was cut too coarsely - say so rather than splitting mid-outcome. That is not this ask.

Do not ask where to cut. The cut is logistics; the user's answer cannot be better informed than the arithmetic. Do not ask when it fits. Do not offer spawn at the start of a feature. Record the chosen mechanism on the same ## Handoff line before the first line of code.

Batches run sequentially and only hand off on green. The next builder reads checks.md and the diff of what landed, never a narrative summary.

When the last batch returns green, the parent dispatches the Verifier in that same turn. Do not ask. A builder never launches it.

What else needs a decision is the profile, a live alternative in Landing, and anything the refuse-rather-than-guess gate caught.

Model tier, only if the harness assigns a model per sub-agent: high reasoning for a core-domain slice and for writing the checks, faster for mechanical slices, mid-to-high for the Verifier - it designs mutations and reasons adversarially, so it is never the cheapest tier. Advisory only; no gate depends on it.

Knowledge chain

In strict order: existing code and conventions, project docs, library documentation (Context7 where available), web search, then flag as uncertain. Never invent an API, a flag, a command or a behaviour. "I could not find documentation for this" always beats a plausible fabrication, because a fabrication propagates into the checks and then into a green test that proves nothing.

Output behaviour

Produce the artifact; do not narrate the phase. Lead with the verdict. State decisions definitively. Cut filler and mechanical hedging. Write the connectives in the language of the document - the section headings are a schema and stay in English, the prose follows the project, and identifiers are never translated.

Examples

Example 1: Plan a feature

User says: "tlc-spec-lean — plan the lockfile v2 migration" Actions:

  1. Read the repository and write .specs/features/lockfile-v2/plan.md (Problem, Flow, Impact, Relations, Surface, Landing, Criteria)
  2. Run python3 <skill-dir>/scripts/validate_plan.py lockfile-v2
  3. Stop for human review — no checks and no code yet

Result: A plan the user can object to. validate_plan.py exits 0. checks.md does not exist.

Example 2: Write the checks and build

User says: "write the checks and build this plan" Actions:

  1. Derive .specs/features/lockfile-v2/checks.md from the approved plan (claims + proofs, Coverage join, Test policy, Swept)
  2. Run python3 <skill-dir>/scripts/validate_checks.py lockfile-v2
  3. Write ## Handoff with the arithmetic. Under the budget: one builder, no ask. Over: stop and ask (handoff vs one builder); record the choice before any code
  4. Write tests from the checks — never from the implementation — then implement, run each proof, and commit
  5. After the last commit of the feature, dispatch a fresh Verifier with verify.md — same turn, no ask. A builder of one batch would have stopped after step 4 instead.

Result: Proof-backed checks, green proofs, coherent commits, and a Verifier report that accounts for every check. The author does not write verification.md.

Example 3: Verify a feature that already landed

User says: "verify work" (recovery — the happy path never waits for this) Actions:

  1. The orchestrator — not the builder — dispatches a fresh Verifier over <feature base>..HEAD with every check
  2. The Verifier writes .specs/features/lockfile-v2/verification.md
  3. Run python3 <skill-dir>/scripts/validate_verification.py lockfile-v2

Result: An independent verification report. validate_verification.py exits 0. Author is not the verifier.

Troubleshooting

Error: a validator exits non-zero

Cause: A structural gate failed — a criterion without SHALL, a check without a proof, a coverage row whose size exceeds its members, a verification report written by the author, or a profile that does not match the approved checks. Solution: Read the script stderr, fix the artifact it named, and re-run the same command. Never skip the script or weaken an assertion to proceed.

Error: no code-execution tool

Cause: The harness cannot run Python. Solution: Perform the same checks by reading the artifact and say once that you are on the degraded path.

© tech-leads-club, CC-BY-4.0. 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 14 other files (scripts, references) in packages/skills-catalog/skills/(development)/tlc-spec-lean of tech-leads-club/agent-skills.

  • SKILL.md
  • references/build.md
  • references/checks.md
  • references/memory.md
  • references/plan.md
  • references/verify.md
  • scripts/check_commit.py
  • scripts/fixtures/checks.md
  • scripts/fixtures/plan.md
  • scripts/fixtures/verification.md
  • scripts/lessons.py
  • scripts/selftest.py
  • scripts/validate_checks.py
  • scripts/validate_plan.py
  • scripts/validate_verification.py

Open the folder on GitHubat commit 6df68d5

Compare with similar skills

Tlc Spec Lean 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.

Tlc Spec Lean compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tlc Spec Lean this skilltech-leads-club/agent-skills7k—~5.1kAutomated safety check: PassCC-BY-4.0
Implementation Plan Writerimbue-ai/bouncer399—~2.1kAutomated safety check: PassAGPL-3.0
Vertical-Slice Task Plannerowainlewis/blueprint412—~1.5kAutomated safety check: PassMIT
Vibe Workflow RouterKhazP/vibe-coding-prompt-template3.1k—~544Automated safety check: NotesMIT
Technical Plan WriterEveryInc/compound-engineering-plugin25k—~1.9kAutomated safety check: PassMIT
Speckit Tasksforyourhealth111-pixel/Vibe-Skills3.6k—~1.6kAutomated safety check: PassApache-2.0

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Questions about Tlc Spec Lean

What does Tlc Spec Lean do?

Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build…. Tlc Spec Lean is an agent skill from tech-leads-club/agent-skills. Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build, then an independent Verifier.

When should I use Tlc Spec Lean?

Tlc Spec Lean fits situations like: the user says tlc-spec-lean; specify feature; write the checks; build this plan.

How do I install Tlc Spec Lean in Claude Code?

Run `npx skills add tech-leads-club/agent-skills --skill tlc-spec-lean -a claude-code`. Or copy the skill folder (packages/skills-catalog/skills/(development)/tlc-spec-lean in tech-leads-club/agent-skills) into .claude/skills/tlc-spec-lean in your project. Claude Code loads it when a task matches its description.

How do I install Tlc Spec Lean in Codex?

Run `npx skills add tech-leads-club/agent-skills --skill tlc-spec-lean -a codex`. Or copy the skill folder (packages/skills-catalog/skills/(development)/tlc-spec-lean in tech-leads-club/agent-skills) into .agents/skills/tlc-spec-lean in your project. Codex loads it when a task matches its description.

Can I use Tlc Spec Lean 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 tech-leads-club/agent-skills --skill tlc-spec-lean -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tlc-spec-lean, .gemini/skills/tlc-spec-lean, .github/skills/tlc-spec-lean and .opencode/skills/tlc-spec-lean in your project.

What does Tlc Spec Lean need to run?

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

Does Tlc Spec Lean 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 Tlc Spec Lean 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 Tlc Spec Lean use?

Tlc Spec Lean is published under the CC-BY-4.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Tlc Spec Lean use?

About 5.1k tokens (SKILL.md is roughly 20k 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 20k tokens, read only when the agent opens those files.

What are the alternatives to Tlc Spec Lean?

Skills that share tags, products or a category with Tlc Spec Lean: Implementation Plan Writer (imbue-ai/bouncer, 399 stars), Vertical-Slice Task Planner (owainlewis/blueprint, 412 stars), Vibe Workflow Router (KhazP/vibe-coding-prompt-template, 3.1k stars) and Technical Plan Writer (EveryInc/compound-engineering-plugin, 25k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Tlc Spec Lean?

tech-leads-club (a GitHub organization) maintains it in tech-leads-club/agent-skills, which has 7,045 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on October 9, 2026.

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