signal-vs-noise-filter

signal-vs-noise-filter is a skill for Claude Code, Codex from fzfclee/consulting-skills. It costs 57 tokens per session (764 once invoked), scanned A, original, Apache-2.0.

A method for separating information that should affect a decision from information that is merely distracting or weakly related. A signal changes the likely explanation, priority, risk, timing, or next action; noise may be true but not useful for the decision.

In plain words
What is it for?
Use it to review observations, identify the facts that matter to a diagnosis or action plan, compare them with a normal baseline, and decide what needs validation.
Why use it?
It helps make sense of situations containing many facts, feelings, events, rumors, or clues without treating every detail as equally important. It also makes missing assumptions and evidence strength visible.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to review observations, identify the facts that matter to a diagnosis or action plan, compare them with a normal baseline, and decide what needs validation.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/fzfclee/consulting-skills/signal-vs-noise-filter
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.

Any agent
npx skills add fzfclee/consulting-skills --skill signal-vs-noise-filter
Clone the repo
git clone --depth 1 https://github.com/fzfclee/consulting-skills

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for signal-vs-noise-filter

README.md
[![agentmods](https://agentmods.dev/badge/skills/fzfclee/consulting-skills/signal-vs-noise-filter/github.svg)](https://agentmods.dev/skills/fzfclee/consulting-skills/signal-vs-noise-filter)
Your own site
<a href="https://agentmods.dev/skills/fzfclee/consulting-skills/signal-vs-noise-filter"><img src="https://agentmods.dev/badge/skills/fzfclee/consulting-skills/signal-vs-noise-filter/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.

agentmods 80×15 button for signal-vs-noise-filter

Your own site · 80×15
<a href="https://agentmods.dev/skills/fzfclee/consulting-skills/signal-vs-noise-filter"><img src="https://agentmods.dev/badge/skills/fzfclee/consulting-skills/signal-vs-noise-filter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 57 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 764 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00057 $0.00764
Opus 5 $0.00028 $0.00382
Sonnet 5 $0.00011 $0.00153
Haiku 4.5 $0.00006 $0.00076

Measured 12d ago against content hash 34c9bc3d1625, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

signal-vs-noise-filter 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 12d 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.

skills/signal-vs-noise-filter/SKILL.md · 79 lines

How it starts

The opening of the file, as written. The whole thing — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Signal vs Noise Filter

Use this skill to identify which observations should change the diagnosis or action plan.

Method Notes

  • A signal is information that changes the likely explanation, priority, risk, timing, or next action.
  • Noise may be true but not decision-relevant.
  • The method works best after an initial evidence map or fact clarification.

Required Inputs

Collect or infer these inputs before execution:

  • decision question or action choice
  • list of observations, events, facts, cues, and concerns
  • baseline expectation before the event
  • timing of key changes
  • available evidence strength

If an input is missing, mark it as missing, state the assumption used, and add a validation action.

When Not To Use

Do not use to repair unreliable evidence or fill basic situation gaps. Use evidence-map when facts, claims, sources, and confidence are mixed; use 5w1h-analysis when who, what, when, where, why, or how is missing. Use this method only after the input is good enough to judge decision relevance.

Step-by-Step Execution

Step Required input How to execute Output
State the baseline Prior expectation, normal pattern, status quo. Clarify what would have happened if nothing material changed. Baseline expectation.
List candidate signals Observations, events, user concerns, timing. Convert each item into a candidate signal. Remove duplicates. Candidate signal list.
Rate decision relevance Decision question, action options. Ask whether this item changes explanation, priority, risk, timing, stakeholder stance, or validation need. Relevance rating.
Rate evidence strength Source, directness, recency, corroboration. Mark each candidate as strong, medium, weak, or missing. Evidence-strength rating.
Separate noise Low-relevance or low-evidence items. Keep true-but-not-actionable items in a noise list so they do not dominate the plan. Noise list.
Name the core signal High-relevance and sufficiently evidenced items. Select the 1-3 signals most likely to change action. Core signal diagnosis.

Read the full file on GitHub · 79 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. 12d ago First seen · 79 lines · 57 tokens per session scan A 34c9bc3d1625

Subscribe to this mod's changes

signal-vs-noise-filter is a skill published in the GitHub repository fzfclee/consulting-skills (4 stars, last pushed 24d ago), licensed Apache-2.0. It adds 57 tokens to every session and 764 once invoked, about $0.0003 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 2026-08-31.