s4h-temporal-timing-analysis

s4h-temporal-timing-analysis is a skill for Claude Code from human-avatar/skills-for-humanity. It costs 62 tokens per session (985 once invoked), scanned A, original, MIT.

A decision guide for judging whether to act now, wait, or prepare based on current conditions and how they are changing.

In plain words
What is it for?
Use it to assess the timing of technical, business, organisational, or other decisions.
Why use it?
It makes timing decisions explicit instead of letting urgency or guesswork decide when to move.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: names the AskUserQuestion tool.

Part of the skills-for-humanity plugin — 197 skills, 1 hook shipped together

Good fit Use it to assess the timing of technical, business, organisational, or other decisions.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/human-avatar/skills-for-humanity/s4h-temporal-timing-analysis
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 human-avatar/skills-for-humanity --skill s4h-temporal-timing-analysis
Clone the repo
git clone --depth 1 https://github.com/human-avatar/skills-for-humanity

Made for: Claude Code.

Or install skills-for-humanity, the plugin that ships this one along with the rest of its 197 skills, 1 hook.

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 s4h-temporal-timing-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-temporal-timing-analysis/github.svg)](https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-temporal-timing-analysis)
Your own site
<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-temporal-timing-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-temporal-timing-analysis/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 s4h-temporal-timing-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-temporal-timing-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-temporal-timing-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 985 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00062 $0.00985
Opus 5 $0.00031 $0.00492
Sonnet 5 $0.00012 $0.00197
Haiku 4.5 $0.00006 $0.00098

Measured 9d ago against content hash f46183d32c6e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

s4h-temporal-timing-analysis 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 9d 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/s4h-temporal-timing-analysis/SKILL.md · 91 lines

How it starts

The opening of the file, as written. The whole thing — 91 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Temporal Timing Analysis

Timing is often as consequential as the decision itself. The right action at the wrong time fails — too early before conditions are ready, too late after the window has closed. Most timing judgments are made implicitly, with the urgency of the moment substituting for analysis. Making timing explicit means identifying which conditions are present, which are absent, and whether the environment is moving toward or away from readiness.


Your Process

Step 1: State the Action and Current Context Name the action under consideration and describe current conditions — market, organizational, political, technical. The timing analysis is grounded in this specific context.

Framing check: Confirm the specific action and context before continuing. State what you've identified — the actual action being timed and the domain it sits in — in one sentence, then use AskUserQuestion:

  • Question: "I'm reading this as: [your one-sentence framing of the action and its current context]. Is that right?"
  • Header: "Framing"
  • Options:
    • Yes — proceed — framing is correct
    • Adjust — one element is off; user will correct it before you continue
    • Reframe — different situation than read; incorporate the correction before proceeding

Step 2: Identify Readiness Conditions What observable conditions would make this optimal timing? These are specific and external — not "when we're ready" but "when X is true in the environment". For each condition: is it currently present or absent?

Step 3: Assess Momentum Is the environment moving toward or away from ideal conditions? A missing condition that is approaching matters differently from one that is receding. Momentum changes the urgency calculation.

Step 4: Cost of Waiting What is lost or foregone per unit of delay? Is the window closing — and how fast? Are competitors moving? Is the opportunity time-limited? Quantify where possible.

Step 5: Cost of Acting Early What risks come from moving before conditions are right? First-mover disadvantage, resource waste, organizational fatigue from premature initiatives, credibility cost of a failed early attempt.

Read the full file on GitHub · 91 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. 9d ago First seen · 91 lines · 62 tokens per session scan A f46183d32c6e

Subscribe to this mod's changes

s4h-temporal-timing-analysis is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 62 tokens to every session and 985 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 2026-09-03.

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