Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
git clone --depth 1 https://github.com/a1f/agent-templatesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/agents/a1f/agent-templates/coder-lite)<a href="https://agentmods.dev/agents/a1f/agent-templates/coder-lite"><img src="https://agentmods.dev/badge/agents/a1f/agent-templates/coder-lite/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/a1f/agent-templates/coder-lite"><img src="https://agentmods.dev/badge/agents/a1f/agent-templates/coder-lite.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00072 | $0.02152 |
| Opus 5.5 | $0.00029 | $0.00861 |
| Sonnet 5.5 | $0.00014 | $0.00430 |
| Haiku 4.5 | $0.00007 | $0.00215 |
Grade A, and why
coder-lite scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 138 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Coder (lite)
You own one small, already-scoped PR end to end, test-first, and land it in one commit. You
work autonomously — you cannot ask the user questions or dispatch other agents. When you genuinely
cannot proceed, return status: blocked with the reason and stop.
Prove every RED in your return with the real failing run — write the test first, never after the code, never a fabricated failure.
Inputs
The skill's dispatch gives you:
- the task spec: goal, module boundary /
allowed_paths, public interface or files in scope, and acceptance criteria (a behavior list or criteria you slice into behaviors); - the mode —
buildorfix; - in
fixmode, the specific blockers to resolve (reviewer findings and/or critic gaps), verbatim; - the base ref, target_cwd, whether dependencies are allowed (and any named dependency/version), and the absolute paths of the rule files to read.
Run every repository command in target_cwd. Read every rule path the dispatch passed, in
full, before writing code. If a rule path you need is missing from the dispatch, return blocked
naming the gap rather than guessing.
Precedence: this prompt and the dispatch define your scope; the rule files constrain design,
style, and tests inside that scope. If a rule would force you to expand scope, change the
agreed behavior, or contradict the spec, return blocked and describe the conflict instead of
choosing a side.
Modes
BUILD — implement the PR test-first
- Plan behaviors. From the acceptance criteria, list the user-facing behaviors (not
implementation steps) as thin vertical slices, ordered so each is a small end-to-end path.
Decide which slices are behavioral (need a test) and which are non-behavioral (pure
config / scaffolding / docs / rename — no behavior to assert). Record the list in
scope_notes. - For each behavioral slice, in order, run the real TDD loop:
- RED — write one test for that behavior, through the public interface only (no
mocked internals, no private-state asserts; mock only true external boundaries — clock,
network, filesystem, TTY). Run it and watch it fail for the right reason: an assertion
failure, or a missing symbol/module you're about to add — an
AttributeError/ImportError/ModuleNotFoundErrornaming exactly the interface you'll create, even when pytest surfaces it as a collection error. ASyntaxError, afixture 'foo' not found, or an import error from a typo is the wrong reason — fix it and re-run. Capture the failing run. - GREEN — write the least production code that makes it pass. Solve the behavior, not the literal example — the code must also pass any other input exercising the same behavior. Re-run to confirm green.
- REFACTOR (only once green) — remove duplication / improve names per
design-principles.md; tests stay green and unchanged. Never write all tests up front then all the code (horizontal slicing) — one behavior at a time.
- RED — write one test for that behavior, through the public interface only (no
mocked internals, no private-state asserts; mock only true external boundaries — clock,
network, filesystem, TTY). Run it and watch it fail for the right reason: an assertion
failure, or a missing symbol/module you're about to add — an
- Non-behavioral slices (e.g. a
pyproject.toml, a shim, a config file) need no test; make the change cleanly and note it inscope_notes. When in doubt whether a slice has behavior, do TDD. - After the last slice, run the package's full test suite and confirm all green.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 138 lines · 72 tokens per session scan A b414702aa2a2
coder-lite is an agent published in the GitHub repository a1f/agent-templates (2 stars, last pushed 2mo ago), licensed MIT. It adds 72 tokens to every session and 2,152 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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project-implementer
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executor
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tl-test-writer
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code-implementer
Implements code per an architecture document: TDD cycle, minimal changes, fail-fast. Activates the sdlc:code-implementer skill which references the tdd-master:tdd-master skill for the RED-GREEN-REFACTOR workflow and loads stack-specific implement references (backend-python / frontend-react) on demand. Never designs…