feature

A workflow for implementing a complete Selectools feature across code, public exports, tests, documentation, examples, and a getting-started notebook.

In plain words
What is it for?
Use it when adding a feature that must be integrated throughout the project and checked against its existing version, tests, examples, and agent architecture.
Why use it?
It reduces the chance that a feature works in code but is missing tests, documentation, examples, or the public interface users need.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/johnnichev/selectools/feature
Any agent
npx skills add johnnichev/selectools --skill feature
Clone the repo
git clone --depth 1 https://github.com/johnnichev/selectools

Made for: Claude Code, Codex.

Per session 20 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,550 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00020 $0.01550
Opus 5 $0.00010 $0.00775
Sonnet 5 $0.00004 $0.00310
Haiku 4.5 $0.00002 $0.00155

Measured 2d ago against content hash 449a00be7ec7, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

feature 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 2d 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.

.claude/skills/feature/SKILL.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Feature Implementation

Implement the following feature: $ARGUMENTS

Live Project State

  • Version: !grep -m1 __version__ src/selectools/__init__.py
  • Tests: !pytest tests/ --collect-only -q 2>/dev/null | tail -1
  • Last example: !ls examples/*.py | tail -1
  • Next example number: use the next zero-padded number after the last one above
  • StepTypes: !python3 -c "from selectools.trace import StepType; print(len(StepType))" 2>/dev/null
  • Observer events: !python3 -c "from selectools.observer import AgentObserver; import inspect; print(len([m for m in dir(AgentObserver) if m.startswith('on_')]))" 2>/dev/null

1. Cross-Feature Impact Analysis

Before writing code, determine:

  • Does this touch agent/core.py? If so, follow the execution flow: _prepare_run → cancellation check → budget check → model selection → on_iteration_start → provider call → _process_response → guardrails → parser → policy → coherence → tool execution → post-tool cancellation check → on_iteration_end
  • Does AgentConfig in agent/config.py need new fields?
  • Does __init__.py need new public exports?
  • Does trace.py need new StepType values? (currently 16)
  • Does observer.py need new events? If so, add to ALL FOUR classes:
    • AgentObserver (no-op default)
    • AsyncAgentObserver (async no-op)
    • LoggingObserver (JSON emission via _emit())
    • SimpleStepObserver (delegate to self._cb())
  • Does AgentResult need new fields?
  • Update tests/test_phase1_design_patterns.py StepType count if adding new types

2. Write Source Code

New module pattern:

"""Module docstring — one line."""

from __future__ import annotations

from dataclasses import dataclass
from typing import Any, Dict, List, Optional

# Lazy imports for optional deps
try:
    import some_lib
except ImportError:
    some_lib = None  # type: ignore[assignment]

For agent loop changes — add to the shared helpers (_check_budget, _build_cancelled_result, etc.) rather than duplicating in run()/arun()/astream(). Use _RunContext to carry per-run state.

Read the full file on GitHub · 157 lines

Changes

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.

  1. 2d ago First seen · 157 lines · 20 tokens per session scan A 449a00be7ec7

Subscribe to this mod's changes

feature is a skill published in the GitHub repository johnnichev/selectools (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 20 tokens to every session and 1,550 once invoked, about $0.0001 per session on Opus 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 2026-08-30.