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 human-avatar/skills-for-humanity --skill s4h-resource-allocation-analysisgit clone --depth 1 https://github.com/human-avatar/skills-for-humanityWrote 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/human-avatar/skills-for-humanity/s4h-resource-allocation-analysis)<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-resource-allocation-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-resource-allocation-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.
<a href="https://agentmods.dev/skills/human-avatar/skills-for-humanity/s4h-resource-allocation-analysis"><img src="https://agentmods.dev/badge/skills/human-avatar/skills-for-humanity/s4h-resource-allocation-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00060 | $0.01017 |
| Opus 5 | $0.00030 | $0.00508 |
| Sonnet 5 | $0.00012 | $0.00203 |
| Haiku 4.5 | $0.00006 | $0.00102 |
Grade A, and why
s4h-resource-allocation-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.
How it starts
The opening of the file, as written. The whole thing — 95 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Resource Allocation Analysis
Every allocation is a trade-off — giving to one thing means giving less to another. The problem is that most allocations are made implicitly, leaving the trade-offs invisible. Making trade-offs explicit forces honest prioritisation and prevents the political habit of pretending everything can be fully funded.
Your Process
Step 1: Inventory Available Resources Name and quantify the resources to be allocated: budget, headcount, time, capacity. Be precise about what is actually available — not what is desired.
Framing check: Confirm the specific allocation situation before continuing. State what resources you've identified and the decision context they apply to in one sentence, then use AskUserQuestion:
- Question: "I'm reading this as: [your one-sentence framing — e.g. 'Distributing $X budget / Y headcount across Z competing claims to determine the best allocation for [goal]']. 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: List All Competing Claims Every demand on the resource. Include maintenance and ongoing commitments, not just new initiatives. Claims that are implicitly assumed to be funded should be made explicit here.
Step 3: Assess Each Claim For each claim: what is the strategic priority (how directly does this serve the most important goals)? What is the cost of under-resourcing it (what breaks, slows, or is lost if it receives less)?
Step 4: Identify Constraints Are there minimums (must have at least X to function), maximums (more than Y produces no additional value), or dependencies (A must be funded before B makes sense)?
Step 5: Draft an Allocation Distribute the available resource across claims. At this stage, make the trade-offs explicit: write down what each claim gives up under this draft allocation.
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.
- 9d ago First seen · 95 lines · 60 tokens per session scan A 80ae624153c2
s4h-resource-allocation-analysis is a skill published in the GitHub repository human-avatar/skills-for-humanity (223 stars, last pushed 1mo ago), licensed MIT. It adds 60 tokens to every session and 1,017 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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