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.
npx skills add oleg494/coding-kit --skill windows-encoding-fixesgit clone --depth 1 https://github.com/oleg494/coding-kitWrote 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/skills/oleg494/coding-kit/windows-encoding-fixes)<a href="https://agentmods.dev/skills/oleg494/coding-kit/windows-encoding-fixes"><img src="https://agentmods.dev/badge/skills/oleg494/coding-kit/windows-encoding-fixes/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/skills/oleg494/coding-kit/windows-encoding-fixes"><img src="https://agentmods.dev/badge/skills/oleg494/coding-kit/windows-encoding-fixes.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 | $0.00108 | $0.02707 |
| Opus 5.5 | $0.00043 | $0.01083 |
| Sonnet 5.5 | $0.00022 | $0.00541 |
| Haiku 4.5 | $0.00011 | $0.00271 |
Grade A, and why
windows-encoding-fixes scanned grade A with 2 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| curl — alias | in PowerShell `curl` = Invoke-WebRequest | `curl.exe` explicitly | Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
**Symptom:** `subprocess.run(["npm", "install", ...])` → How it starts
The opening of the file, as written. The whole thing — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Windows: encodings, console, cross-platform
Experience from two coding-kit installation bug reports on Windows 10 (research.db id=141, 146). Each pitfall — with symptom, cause, fix. Apply to ANY script/file that must also work on Windows.
1. stdout encoding: cp1251 kills Russian output
Symptom: UnicodeEncodeError: '\u2713' ... codec can't encode — fails
when printing ✓/✗/Cyrillic. Shows up when redirecting output
(script > log 2>&1) and in a cp1251 console.
Cause: the Windows console defaults to cp1251; Python 3.12 takes the console encoding when redirecting, and Unicode does not fit into it.
Fix (required in every CLI script):
try:
sys.stdout.reconfigure(encoding="utf-8", errors="replace")
sys.stderr.reconfigure(encoding="utf-8", errors="replace")
except Exception: # noqa: S110,BLE001 — reconfigure is optional
pass
In coding-kit — the single memory/scripts/_compat.py: fix_encoding() instead of copying.
Fix for bash wrappers:
export PYTHONIOENCODING="${PYTHONIOENCODING:-utf-8}"
System-level fix (recommended for every Windows box):
[Environment]::SetEnvironmentVariable("PYTHONUTF8", "1", "User")
2. Writing files: CRLF breaks md5 checks
Symptom: Path.write_text() on Windows writes \r\n; the canonical form is \n.
Any md5 check of mirrors/copies falsely fails with «files diverged».
Fix when writing: newline="\n" + byte comparison:
dst.write_text(content, encoding="utf-8", newline="\n")
# freshness check:
if dst.read_bytes() == content.encode("utf-8"): ...
Fix when checking (bash, md5 with normalization):
first=$(tr -d '\r' < "${MIRRORS[0]}" | md5sum | cut -d' ' -f1)
3. PowerShell 5.1: UTF-8 without BOM is read as cp1251
Symptom: a bootstrap .ps1 ignores --check, outputs mojibake,
fails on the dash «—» in comments.
Cause: Windows PowerShell 5.1 decodes a .ps1 without BOM as cp1251; Cyrillic and dashes break parsing (down to the argument logic).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 2d ago Changed a14c32e80cbf
- 8d ago Changed 27e7b5894145
- 11d ago Changed 480bc6686380
- 25d ago Changed e64b75e903ae
- 26d ago Changed 6a713d5036d0
- 1mo ago Changed d0e8a972b675
- 1mo ago Changed 6978b0b9a435
- 1mo ago Changed 1d2af3efec51
- 1mo ago Changed ab898bcb767d
- 1mo ago First seen · 234 lines · 108 tokens per session scan A 67f4661df876
windows-encoding-fixes is a skill published in the GitHub repository oleg494/coding-kit (3 stars, last pushed 2d ago), licensed MIT. It adds 108 tokens to every session and 2,707 once invoked, about $0.0004 per session on Opus 5.5. A static security scan graded it A with 2 findings (makes network calls, runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
spae-fix
Remediates pre-classified SPAE task gaps. Use after /check writes FIX.md and moves an active task to phase fix.
troubleshoot
Troubleshoot systematically: observe, hypothesize, test, fix, verify.
refactor
Refactor code to fix DRY, SOLID, and Structure violations while preserving behavior.
tracely
Instrument AI agents with Tracely and turn their production traces into CI gates. Use when the user mentions Tracely, tracely-ai, tracelysdk, the tracely CLI, or asks to trace/observe an AI agent, add LLM evaluators or LLM-as-a-judge columns, debug why a trace or conversation isn't showing up, wire agent regression…
debugging-livekit-agents
Drives a multi-turn conversation with a LiveKit agent running locally to see what it does. Use when the user says "test my agent", "try my agent", "does this work", "why did it call that tool", "it says the wrong thing when I ask X", "test this change", or whenever you have edited an agent and need to check how it…
gcloud-usage
This skill should be used when user asks about "GCloud logs", "Cloud Logging queries", "Google Cloud metrics", "GCP observability", "trace analysis", or "debugging production issues on GCP".