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 acaprino/daodan --skill abstraction-architectgit clone --depth 1 https://github.com/acaprino/daodanWrote 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/acaprino/daodan/abstraction-architect)<a href="https://agentmods.dev/skills/acaprino/daodan/abstraction-architect"><img src="https://agentmods.dev/badge/skills/acaprino/daodan/abstraction-architect/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/acaprino/daodan/abstraction-architect"><img src="https://agentmods.dev/badge/skills/acaprino/daodan/abstraction-architect.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 | $0.00204 | $0.01122 |
| Opus 5 | $0.00102 | $0.00561 |
| Sonnet 5 | $0.00041 | $0.00224 |
| Haiku 4.5 | $0.00020 | $0.00112 |
Grade A, and why
abstraction-architect 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 10d 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 — 70 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Abstraction Architect Knowledge Base
The question this knowledge base answers:
Where is the same concept represented, owned, computed or implemented more than once, and what does it cost when that concept changes?
Structural entropy accumulates in ways that look locally reasonable. A support team implements an eligibility check because the domain one was hard to reach. A config value is added next to the code that reads it. A DTO is copied because the original had a field the new caller did not want. Each decision is defensible; the sum is a codebase where a single conceptual change touches nine files and misses two.
The two evidence tracks
Everything here rests on one distinction, developed in references/theory.md section 9 and operationalized in references/evidence-tracks.md.
The track determines the nature of the evidence. The dimension determines the gate.
- Form is the same mechanism written more than once. The risk is premature extraction, the instrument is the count, and the Rule of Three is the gate for D5.
- Knowledge is the same fact holding more than one authoritative representation. The risk is drift between owners, the count is the wrong instrument, and two representations are sufficient behind a much stricter semantic proof.
The discriminating question for the knowledge track: can these representations legitimately disagree? If yes, there is no finding, whatever the surface similarity. If no, two is enough.
When to use this skill
Load it when:
- Deciding whether to extract, centralize or inline
- Asking who canonically owns a fact, a policy, a threshold or a piece of state
- Auditing for duplicated knowledge, competing authorities, redundant models, or stored state that is derivable
- Evaluating whether an existing abstraction is paying for itself
- Running
/abstraction-architect:audit, which spawns the auditor agent that loads this skill
Do not load it for the concerns listed in references/scope-boundaries.md, which names the owner of each.
What ships with it
11 files 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.
- references/anti-patterns.md 25 KB
- references/concept-census.md 4.6 KB
- references/concept-index-protocol.md 10 KB
- references/decision-frame.md 5.1 KB
- references/dimensions.md 8.9 KB
- references/evidence-tracks.md 4.9 KB
- references/further-reading.md 7.1 KB
- references/scope-boundaries.md 3.5 KB
- references/theory.md 25 KB
- references/unification-patterns.md 42 KB
- scripts/concept_index.py 18 KB runs code
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.
- 10d ago First seen · 70 lines · 204 tokens per session scan A 5af18fdfccdb
abstraction-architect is a skill published in the GitHub repository acaprino/daodan (9 stars, last pushed yesterday), licensed MIT. It adds 204 tokens to every session and 1,122 once invoked, about $0.0010 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.
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