Grad Agenda Setting

What it does

When your agent uses it

• The user needs to study media influence on public opinion priorities
• Evaluate issue salience transfer across media and public agendas
• Design communication strategies that leverage agenda-setting effects — even if they say why is everyone talking about this topic
• How does media shape public priorities

Example prompts

• “why is everyone talking about this topic”
• “how does media shape public priorities”
• “which issues get attention and why”
• “/grad-agenda-setting”

Workflow steps

4 steps, taken from the step headings in SKILL.md.

1. 1Identify Agendas
2. 2Measure Salience
3. 3Analyze Transfer
4. 4Assess Contingent Conditions

What it can do on your machine

Read from SKILL.md and the folder at commit 4e7f4f8. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Grad Agenda Setting loads about 1.1k tokens when it runs, and up to ~6.5k if it reads all its reference files. Until then it costs about 125 tokens; SKILL.md has 329 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~125

When it runs · the whole SKILL.md, loaded when a task matches

~1.1k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~6.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from asgard-ai-platform/skills at commit 4e7f4f8, republished under its MIT licence (© asgard-ai-platform). 329 words, ~1,110 tokens.

name

grad-agenda-setting

description

Apply agenda-setting theory (McCombs & Shaw) to analyze how media salience transfers to public perception. Use this skill when the user needs to study media influence on public opinion priorities, evaluate issue salience transfer across media and public agendas, or design communication strategies that leverage agenda-setting effects — even if they say 'why is everyone talking about this topic', 'how does media shape public priorities', or 'which issues get attention and why'.

metadata.category

WP-33 傳播/教育/公共行政

metadata.tags

communication, agenda-setting, media-effects, public-opinion

IRON LAW: Media May Not Tell People WHAT to Think, But It Tells Them WHAT TO THINK ABOUT

Issue salience is transferred from media to public agenda. The MORE
coverage an issue receives, the MORE important the public perceives it
to be — regardless of objective importance. This operates at two levels:
1. First level: OBJECT salience (which issues matter)
2. Second level: ATTRIBUTE salience (which aspects of issues matter)

# Agenda-Setting Analysis: {Issue/Context}

## Media Agenda
- Issues ranked by salience: {list with coverage metrics}
- Time period: {dates analyzed}
- Sources: {media outlets examined}

## Public Agenda
- Issues ranked by perceived importance: {survey/social data}
- Measurement method: {MIP survey, social media analysis, etc.}

## Salience Transfer
- Correlation: {media-public agenda correlation}
- Time lag: {observed lag period}
- Direction: {media→public, public→media, or intermedia}

## Moderating Factors
- Need for orientation: {high/low and why}
- Issue obtrusiveness: {obtrusive vs unobtrusive}

## Implications
{Strategic recommendations based on findings}

© asgard-ai-platform, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (references) in grad-agenda-setting of asgard-ai-platform/skills.

• SKILL.md
• examples/sample_scenario.md
• references/advanced-models.md
• references/content-analysis.md

Open the folder on GitHubat commit 4e7f4f8