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 Kshitijpalsinghtomar/depth-skills --skill ds-shallowgit clone --depth 1 https://github.com/Kshitijpalsinghtomar/depth-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/kshitijpalsinghtomar/depth-skills/ds-shallow)<a href="https://agentmods.dev/skills/kshitijpalsinghtomar/depth-skills/ds-shallow"><img src="https://agentmods.dev/badge/skills/kshitijpalsinghtomar/depth-skills/ds-shallow/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/kshitijpalsinghtomar/depth-skills/ds-shallow"><img src="https://agentmods.dev/badge/skills/kshitijpalsinghtomar/depth-skills/ds-shallow.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 | $0.00024 | $0.01086 |
| Opus 5 | $0.00012 | $0.00543 |
| Sonnet 5 | $0.00005 | $0.00217 |
| Haiku 4.5 | $0.00002 | $0.00109 |
Grade A, and why
shallow 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 11d 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 — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SHALLOW — Proportional Depth Protocol
DEEP-THINK is essential. But not every task deserves it. Sometimes the deepest answer is a short one.
The failure mode of depth-skills is depth bias: the model reaches for sophisticated analysis on problems that don't warrant it. A CSS color choice gets 6-step reasoning. A routine email gets threat-modeled. This skill is the brake.
The Failure Mode You Must Recognize
You are about to:
- Generate six artifacts for a question that could be answered in one sentence
- Add caveats to a decision that is easily reversed
- Apply THRESHOLD analysis to a temporary workaround
- Treat a first-pass response as if it were a permanent architecture decision
If the cost of being wrong is low and the fix is easy — this is a SHALLOW task.
The Protocol
1 — ASSESS DEPTH APPROPRIATENESS
Evaluate the task against depth criteria:
DEPTH ASSESSMENT
────────────────────────────────────────
Reversibility: [Trivial / Moderate / Hard / Permanent]
→ If Trivial/Moderate: favor SHALLOW
Consequence: [Trivial / Moderate / Significant / Critical]
→ If Trivial/Moderate: favor SHALLOW
Complexity: [Simple / Moderate / Complex / Intricate]
→ If Simple: favor SHALLOW
Pattern match: [Routine / Variation / Novel / Unprecedented]
→ If Routine: favor SHALLOW
Stakeholders: [One / Few / Many / All-hands]
→ If One/Few: favor SHALLOW
Urgency: [Can wait / Within hour / Within minute / Now]
→ If "can wait" is false: favor SHALLOW (speed matters)
────────────────────────────────────────
Score: Count SHALLOW-favoring answers.
- 0-1: Deep task — use DEEP-THINK
- 2-3: Mixed — use abbreviated deep analysis
- 4-6: Shallow task — use this protocol
Artifact: Depth assessment with score. Step 2 allocates budget.
2 — ALLOCATE COGNITIVE BUDGET
Based on the assessment, allocate:
BUDGET ALLOCATION
────────────────────────────────────────
Assessment score: [N]/6
Depth budget: [MINIMAL / LIGHT / MODERATE]
MINIMAL (score 5-6):
- No artifacts required
- One sentence answer
- Skip caveats
- Skip alternatives
- Skip "it depends"
LIGHT (score 3-4):
- One artifact: answer with ONE assumption stated
- One alternative mentioned in 1 sentence
- One caveat if genuinely important
MODERATE (score 2-3):
- Two artifacts: restatement + chosen approach
- Skip challenge phase
- Minimal boundary check
────────────────────────────────────────
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.
- 11d ago First seen · 146 lines · 24 tokens per session scan A 60c203b54a5d
shallow is a skill published in the GitHub repository Kshitijpalsinghtomar/depth-skills (4 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 1,086 once invoked, about $0.0001 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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