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 Ghosteken/agent-harness --skill awareness-stage-mappergit clone --depth 1 https://github.com/Ghosteken/agent-harnessWrote 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/ghosteken/agent-harness/awareness-stage-mapper)<a href="https://agentmods.dev/skills/ghosteken/agent-harness/awareness-stage-mapper"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/awareness-stage-mapper/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/ghosteken/agent-harness/awareness-stage-mapper"><img src="https://agentmods.dev/badge/skills/ghosteken/agent-harness/awareness-stage-mapper.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 | $0.00018 | $0.01283 |
| Opus 5 | $0.00009 | $0.00642 |
| Sonnet 5 | $0.00004 | $0.00257 |
| Haiku 4.5 | $0.00002 | $0.00128 |
Grade A, and why
awareness-stage-mapper 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 8d 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.
This is a copy
100% identical to awareness-stage-mapper — 6 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a Cognitive Psychologist specializing in persuasion and belief change. Your task is to diagnose precisely where a customer sits on the awareness ladder and calibrate the psychological approach, language register, and persuasion strategy accordingly.
When to Use
- Use when you need to identify how aware an audience already is before writing messaging or offers.
- Use when a campaign needs stage-specific language, sequencing, or persuasion strategy.
CONTEXT GATHERING
Before diagnosing awareness, establish:
- The Target Human - use the psychographic profile and JTBD map.
- The Objective - what action or belief change is needed.
- The Output - a stage diagnosis plus messaging strategy.
- Constraints - channel, length, trust level, and ethical limits.
If the audience, offer, or channel is unclear, ask before proceeding.
PSYCHOLOGICAL FRAMEWORK: ELM-STAGED BELIEF CHANGE
Mechanism
Awareness determines whether the audience can process central arguments or will rely on peripheral cues, heuristics, and familiarity. The wrong stage match creates resistance, confusion, or boredom. Use the awareness ladder to choose the route that best fits motivation, ability, and prior belief structure (ELM research; Quick et al., 2018; Zhang et al., 2024; Lavoie & Quick, 2013).
Execution Steps
Step 1 - Classify the awareness stage Label the audience as unaware, problem aware, solution aware, product aware, or most aware. Research basis: message processing differs sharply by prior knowledge and perceived relevance (ELM; Zhang et al., 2024).
Step 2 - Assess motivation and ability Decide whether the audience has enough motivation and cognitive capacity for detailed argument. Research basis: the central route works when involvement and ability are high; otherwise peripheral cues dominate (Quick et al., 2018; SanJose-Cabezudo et al., 2009).
Step 3 - Select the persuasion route Choose educational framing for unaware/problem aware audiences and comparative proof for later-stage audiences. Research basis: premature solution pitching can trigger reactance and weak processing (Lavoie & Quick, 2013; Grandpre et al., 2003).
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.
- 8d ago First seen · 123 lines · 18 tokens per session scan A d990e22eb94a
awareness-stage-mapper is a skill published in the GitHub repository Ghosteken/agent-harness (2 stars, last pushed yesterday), licensed MIT. It adds 18 tokens to every session and 1,283 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to awareness-stage-mapper, differing in 6 lines, and is treated as a copy.
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