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 agentmods add skills/t1/tdder/appnpx skills add t1/tdder --skill appgit clone --depth 1 https://github.com/t1/tdderWhat 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 | $0.00062 | $0.00776 |
| Opus 5 | $0.00031 | $0.00388 |
| Sonnet 5 | $0.00012 | $0.00155 |
| Haiku 4.5 | $0.00006 | $0.00078 |
Grade A, and why
app 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 2d 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 — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Absolute Priority Premise (APP)
Objective heuristic for comparing code quality by assigning mass values to code components. Lower total mass indicates simpler code.
The Six Components
| Component | Mass | Examples |
|---|---|---|
| Constant | 1 | 5, "hello", true, [] |
| Binding | 1 | amount, userName, result |
| Invocation | 2 | calculate(), Math.max(a, b) |
| Conditional | 4 | if, switch, case, ?: |
| Loop | 5 | while, for, forEach, map |
| Assignment | 6 | x = 5, count++, list.add() |
Calculation
Total Mass = (constants x 1) + (bindings x 1) + (invocations x 2)
+ (conditionals x 4) + (loops x 5) + (assignments x 6)
Lower mass = Better code (all else being equal).
Special Counting Rules
- Method declarations count as Constant (1) + Binding (1)
- Class definitions count as Constant (1) + Binding (1) (usually ignored in comparisons)
finalfields and local variables are Bindings (1), not Assignments (6)- Only re-assignments that modify values count as Assignment (6)
Integration with TDD
- Red Phase: Mass is irrelevant (focus on passing tests)
- Green Phase: Minimal code naturally has low mass
- Refactor Phase: Use APP to guide toward simpler solutions
Integration with Simple Design
- Tests Pass (Rule #1) - Always highest priority
- Reveals Intent (Rule #2) - May increase mass for clarity
- No Duplication (Rule #3) - Extract to reduce mass
- Fewest Elements (Rule #4) - Aligns with low mass goal
Simple Design Rule #2 trumps APP - Choose clarity over low mass. APP helps choose between equivalent clear solutions.
When to Apply
- During refactoring to choose between working solutions
- When comparing algorithms of similar functionality
- To guide toward simpler implementations
When NOT to Apply
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.
- 2d ago First seen · 84 lines · 62 tokens per session scan A d63bc6cea6ce
app is a skill published in the GitHub repository t1/tdder (14 stars, last pushed 2d ago), licensed Apache-2.0. It adds 62 tokens to every session and 776 once invoked, about $0.0003 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 2026-08-30.
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