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 charlieviettq/awesome-agent-skill --skill grad-affordancegit clone --depth 1 https://github.com/charlieviettq/awesome-agent-skillWrote 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/charlieviettq/awesome-agent-skill/grad-affordance)<a href="https://agentmods.dev/skills/charlieviettq/awesome-agent-skill/grad-affordance"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/grad-affordance/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/charlieviettq/awesome-agent-skill/grad-affordance"><img src="https://agentmods.dev/badge/skills/charlieviettq/awesome-agent-skill/grad-affordance.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00106 | $0.01146 |
| Opus 5 | $0.00053 | $0.00573 |
| Sonnet 5 | $0.00021 | $0.00229 |
| Haiku 4.5 | $0.00011 | $0.00115 |
Grade A, and why
"grad-affordance" 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Affordance Theory (Gibson / Norman)
Overview
Affordance Theory explains how actors perceive and realize action possibilities offered by objects or environments. Gibson's ecological view holds that affordances are relational properties existing between actor and environment, independent of perception. Norman adapted the concept for design — perceived affordances guide user interaction, and signifiers communicate where action is possible. In IS research, affordance theory explains how technology enables (or constrains) organizational action.
When to Use
- Analyzing why users can or cannot effectively use a technology
- Designing interfaces that communicate functionality clearly
- Explaining how the same technology produces different outcomes in different organizations
- Bridging the gap between technology features and organizational practices
When NOT to Use
- Predicting adoption likelihood (use TAM/UTAUT)
- Measuring usability metrics quantitatively (use SUS or heuristic evaluation)
- When the focus is purely on aesthetic design without functional implications
Assumptions
IRON LAW: An affordance exists in the RELATION between actor and artifact —
it is neither a property of the object alone nor of the user alone.
Key assumptions:
- Affordances are relational — they depend on both artifact properties and actor capabilities
- Affordance existence differs from affordance perception differs from affordance actualization
- The same technology affords different actions to different actors (role, skill, goal-dependent)
- Constraints are the complement of affordances — what the artifact prevents or discourages
Methodology
Step 1 — Identify actors and artifacts
Specify the technology artifact and the actor groups. Characterize actor capabilities, goals, and context. The same artifact affords different things to a novice versus an expert.
Step 2 — Enumerate affordances
For each actor-artifact pair, identify:
| Affordance Type | Description |
|---|---|
| Existence | What action possibilities objectively exist in the relation |
| Perception | Which affordances actors actually perceive (Norman's focus) |
| Actualization | Which perceived affordances actors act upon |
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 · 111 lines · 106 tokens per session scan A e6721bd9c7ed
"grad-affordance" is a skill published in the GitHub repository charlieviettq/awesome-agent-skill (25 stars, last pushed 1mo ago), licensed MIT. It adds 106 tokens to every session and 1,146 once invoked, about $0.0005 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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