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 Dragoon0x/taste-skills --skill self-assessmentgit clone --depth 1 https://github.com/Dragoon0x/taste-skillsWrote 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/dragoon0x/taste-skills/self-assessment)<a href="https://agentmods.dev/skills/dragoon0x/taste-skills/self-assessment"><img src="https://agentmods.dev/badge/skills/dragoon0x/taste-skills/self-assessment/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/dragoon0x/taste-skills/self-assessment"><img src="https://agentmods.dev/badge/skills/dragoon0x/taste-skills/self-assessment.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 | $0.00037 | $0.00350 |
| Opus 5.5 | $0.00015 | $0.00140 |
| Sonnet 5.5 | $0.00007 | $0.00070 |
| Haiku 4.5 | $0.00004 | $0.00035 |
Grade A, and why
self-assessment 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 2mo 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.
What it actually says
Self-Assessment
Know your gaps. Practice the right thing.
How to use
/self-assessmentGenerate a taste self-assessment for the user.
Constraints
Six Skill Areas
Rate 1-5 on each:
- Seeing: Can you spot spacing inconsistencies, hierarchy issues, and craft details without being told?
- Comparing: Can you rank solutions and explain the ranking beyond personal preference?
- Deconstructing: Can you reverse-engineer the constraints and decisions behind a design?
- Collecting: Do you have an organized, principle-tagged reference library you can search in 60 seconds?
- Articulating: Can you explain design decisions without saying "it feels right"?
- Applying: Does your first design instinct usually turn out to be correct?
Interpreting Results
- Lowest score = where to focus. Don't improve everything at once.
- High Seeing + Low Articulating = good instincts, can't convince anyone. Focus on vocabulary.
- High Collecting + Low Applying = great references, own work doesn't match. Focus on deconstruction.
- Even scores across the board (all 2s or 3s) = the plateau. Go deep in any one area.
- MUST retake every 3 months. Taste develops too slowly to notice daily.
Anti-Patterns
- Overrating yourself on every dimension
- Skipping the assessment and jumping straight to exercises
- Focusing only on strengths instead of weaknesses
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.
- 2mo ago First seen · 36 lines · 37 tokens per session scan A 835c5cf15ecc
self-assessment is a skill published in the GitHub repository Dragoon0x/taste-skills (7 stars, last pushed 8mo ago), licensed MIT. It adds 37 tokens to every session and 350 once invoked, about $0.0001 per session on Opus 5.5. 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.
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