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-descendgit 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-descend)<a href="https://agentmods.dev/skills/kshitijpalsinghtomar/depth-skills/ds-descend"><img src="https://agentmods.dev/badge/skills/kshitijpalsinghtomar/depth-skills/ds-descend/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-descend"><img src="https://agentmods.dev/badge/skills/kshitijpalsinghtomar/depth-skills/ds-descend.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 | $0.04060 |
| Opus 5.5 | $0.00015 | $0.01624 |
| Sonnet 5.5 | $0.00007 | $0.00812 |
| Haiku 4.5 | $0.00004 | $0.00406 |
Grade A, and why
descend 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 24d 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 — 467 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DESCEND v2.0 — Pattern Audit & First-Principles Derivation (Premium)
Mathematical Compliance: This skill implements the DEPTH-MATHEMATICS specification. It computes and outputs ADS phase activation, CEI components, SI components, cognitive traces (activation heatmap, assumption dependency graph), and verifies Gates V1, V2, V3. It integrates with BOUNDARY-DETECTOR for knowledge boundary probes.
Every answer you generate is built from patterns — compressed experience retrieved from training: "In situations like X, do Y." This is efficient when the match is real.
It is catastrophic when it isn't. And you do not check.
Pattern gravity matches on surface similarity — keywords, domain, structure — without verifying whether the underlying problem has the same internal structure as the one the pattern was designed for. Problems that look alike on the surface can have completely different mechanics underneath. The pattern that solved one will silently damage the other.
This skill has two phases:
- Phase 1: AUDIT — is the pattern match real, or is it a surface-level false analogy?
- Phase 2: DERIVE — if the match is false, reason from fundamental truths upward.
New in v2.0: Mathematical depth metrics, recursive self-audit, cognitive trace artifacts, verification gates, boundary detection integration.
The Failure Mode You Must Recognize
You are about to generate a response that:
- Applies a pattern unconsciously without verifying its preconditions
- Forces a familiar template onto a problem with different internal structure
- Claims "this is just like [previous problem]" without checking structural preconditions
- Produces derivation artifacts without genuine first-principles reasoning (cargo cult derivation)
If you recognize this pattern forming — you are in unconscious analogy. Continue with the protocol.
The Protocol
0 — PARAMETERIZE: Read Thinking Parameters
Read thinking_parameters:
min_preconditions(default 3) — minimum preconditions to checkmin_break_points(default 1) — minimum break points to identifyrecursion_depth(default 1) — recursive self-audit roundsrequire_derivation(default true) — must produce derivation stackrequire_reconciliation(default true) — must reconcile with abandoned patterns
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.
- 24d ago Changed · +265 lines · +16 tokens per session 6049f22c75a4
- 1mo ago First seen · 202 lines · 21 tokens per session scan A 1889211f4b44
descend is a skill published in the GitHub repository Kshitijpalsinghtomar/depth-skills (5 stars, last pushed 13d ago), licensed MIT. It adds 37 tokens to every session and 4,060 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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