Policy Brief

Policy Brief is a skill for Claude Code, Codex from SkillMedev/academic-researcher. It costs 121 tokens per session (1,315 once invoked), scanned A, original, MIT.

A short decision document that explains a public problem, compares possible responses using the same criteria, and recommends an action based on evidence.

In plain words
What is it for?
Use it to brief a minister, board, council, or other decision-maker on a specific policy choice.
Why use it?
It lets a busy decision-maker understand the choice, supporting evidence, and trade-offs quickly without reading a full report.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: positional $N argument.

Good fit Use it to brief a minister, board, council, or other decision-maker on a specific policy choice.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/skillmedev/academic-researcher/policy-brief
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 SkillMedev/academic-researcher --skill policy-brief
Clone the repo
git clone --depth 1 https://github.com/SkillMedev/academic-researcher

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 Policy Brief

README.md
[![agentmods](https://agentmods.dev/badge/skills/skillmedev/academic-researcher/policy-brief/github.svg)](https://agentmods.dev/skills/skillmedev/academic-researcher/policy-brief)
Your own site
<a href="https://agentmods.dev/skills/skillmedev/academic-researcher/policy-brief"><img src="https://agentmods.dev/badge/skills/skillmedev/academic-researcher/policy-brief/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 Policy Brief

Your own site · 80×15
<a href="https://agentmods.dev/skills/skillmedev/academic-researcher/policy-brief"><img src="https://agentmods.dev/badge/skills/skillmedev/academic-researcher/policy-brief.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 121 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,315 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 $0.00121 $0.01315
Opus 5 $0.00060 $0.00658
Sonnet 5 $0.00024 $0.00263
Haiku 4.5 $0.00012 $0.00131

Measured 11d ago against content hash f49bca5900bb, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

Policy Brief 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 11d 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/policy-brief/SKILL.md · 67 lines

How it starts

The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Policy Brief

A brief exists to inform one specific choice by one specific decision-maker - not to survey a literature. The costly failure is the brief that is read only as far as its summary and gives the reader nothing actionable there, or that strawmans the rejected options and loses credibility the moment a stakeholder notices. Write so that a busy reader who stops after the first half-page still knows the problem, the recommendation, and why.

Inputs to collect

  1. Who decides, and what decision they face - the single question the brief must answer. If the user cannot name the decision, help them narrow it before writing; "inform them about X" is not a decision.
  2. The decision deadline and any political, budget, or legal constraints that rule options in or out.
  3. The evidence available: studies, data, prior evaluations. Note what is missing; gaps shape how strongly the brief can recommend.
  4. The audience's technical depth. Default: intelligent non-specialist - define every acronym on first use.
  5. Length target. Default: one to four pages. Longer than four pages is a report, not a brief.

Label anything assumed rather than supplied.

Operating procedure

Order matters: options cannot be compared until criteria are fixed, and the executive summary is written last even though it appears first.

  1. Fix the decision and criteria. State the choice in one sentence. Choose 3-5 comparison criteria - effectiveness, cost, equity, feasibility, time-to-impact are the standard set - and hold them constant across every option.
  2. Draft the problem statement. What is wrong, who is affected, why now, and the cost of inaction. Quantify wherever possible; a problem without a number invites indefinite delay.
  3. Compress the background. Only what is needed to understand the problem - typically one to two paragraphs.
  4. Assemble the evidence. Cite credible primary sources; note the strength and limitation of each. Distinguish strong causal evidence (randomized or well-identified quasi-experimental) from correlation and from expert opinion, and say which is which. Present evidence on all sides, including findings inconvenient to the eventual recommendation.
  5. Build 2-4 realistic options, always including the status quo. For each: how it works, expected impact, cost, feasibility, key trade-offs - scored against the fixed criteria in a comparison table. Do not strawman the options you reject; state each option's best case fairly.
  6. Recommend and condition. Name the preferred option, the reasoning against the criteria, the assumptions it rests on, and the conditions under which the recommendation would change.
  7. Sketch implementation. Concrete first steps, owners, and timeline - a recommendation without a first step is a suggestion.
  8. Write the executive summary last. Problem plus recommendation in 3-4 sentences that stand alone. Many readers read nothing else.

Read the full file on GitHub · 67 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. 11d ago First seen · 67 lines · 121 tokens per session scan A f49bca5900bb

Subscribe to this mod's changes

Policy Brief is a skill published in the GitHub repository SkillMedev/academic-researcher (3 stars, last pushed 2mo ago), licensed MIT. It adds 121 tokens to every session and 1,315 once invoked, about $0.0006 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.

Related

Other skills, from other repositories

aigc-detector

Academic paper AI content detection, rewriting, and thesis writing assistant. Analyzes text for AI-generated characteristics, provides detailed rewrite suggestions, and generates full thesis drafts. Supports .docx files, outputs reports and rewritten/formatted documents. Bilingual: Chinese & English.

free-revalution/AIGC-Detector-Pro · 60 tokens

apollo-prospecting

Use when executing your B2B prospecting strategy inside Apollo.io specifically - turning an ICP into stacked Apollo search filters, building and tiering Apollo Lists, finding and verifying emails with credit discipline, tracking buying signals via Apollo filters and saved-search alerts, and running multi-step Apollo…

SkillMedev/skills · 224 tokens

Cold Email Deliverability

Sets up and protects cold-outbound sending infrastructure - dedicated lookalike domains, SPF/DKIM/DMARC authentication, 2-4 week mailbox warm-up, 30-50 sends/day per-mailbox caps, and continuous bounce/complaint monitoring, with a runnable DNS audit script. Use when someone says "my emails are going to spam", "set up…

SkillMedev/skills · 190 tokens

gym-meta-ads-funnel

Write gym Meta (Facebook/Instagram) ad creative, structure the lead-to-consult funnel, set the budget, and read funnel costs against the challenge economics. Use when a gym owner asks to write Facebook/Instagram ads, says ads aren't converting or cost per lead is too high, asks what to spend on ads, or wants to build…

SkillMedev/skills · 132 tokens

gym-money-model

Model gym unit economics - Client-Financed Acquisition, 30-day cash, CAC, LTV, LTV:CAC, and payback - and return a verdict on whether growth self-funds. Use when a gym owner asks "what's my CAC", "how much can I spend to get a member", "what should my challenge cost to break even", "is my gym profitable to scale"…

SkillMedev/skills · 127 tokens

A/B Test Analyzer

Analyzes an A/B experiment to a defensible verdict - sample-size and minimum-detectable-effect math, two-proportion significance testing with confidence intervals, and checks for the traps that fake a win (peeking, sample ratio mismatch, multiple comparisons). Use when someone asks "is this test significant", "did…

SkillMedev/skills · 142 tokens