Recon Skills is a pack of security-testing skills covering reconnaissance, web applications, APIs, authentication, vulnerability validation, cloud infrastructure, and reporting. Security professionals use it for authorized assessments of systems they own or have written permission to test. The catalogue entries are individual skills from the pack.
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 uphiago/recon-skills --skill cross-wave-delta-analysisgit clone --depth 1 https://github.com/uphiago/recon-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/uphiago/recon-skills/cross-wave-delta-analysis)<a href="https://agentmods.dev/skills/uphiago/recon-skills/cross-wave-delta-analysis"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/cross-wave-delta-analysis/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/uphiago/recon-skills/cross-wave-delta-analysis"><img src="https://agentmods.dev/badge/skills/uphiago/recon-skills/cross-wave-delta-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00021 | $0.01251 |
| Opus 5 | $0.00010 | $0.00626 |
| Sonnet 5 | $0.00004 | $0.00250 |
| Haiku 4.5 | $0.00002 | $0.00125 |
Grade A, and why
cross-wave-delta-analysis 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 12d 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Cross-Wave Delta Analysis Skill
Methodology for comparing findings across multiple recon waves on the same target set. Detects NEW findings, REGRESSIONS (previously open now blocked), PERSISTENT vulnerabilities, and CHANGES over time. Distilled from 9 waves across 7 deep targets that revealed missed CORS findings, new port exposures, and infrastructure drift.
When to Use
- Running repeated recon on the same target set (Wave N+1 after Wave N).
- You want to know if a vulnerability was PATCHED since last wave.
- You want to know if a NEW surface appeared (new ports, new subdomains, new endpoints).
- After completing a deep recon wave — produce the delta report before next wave.
- Before reporting — confirm findings are still valid (not regressed).
Prerequisites
- Prior assessment output beneath
${OUTPUT_DIR:-./output}/baseline/. - Current assessment output beneath
${OUTPUT_DIR:-./output}/current/. - Structured findings per target (at minimum: ports, CORS status, WP users, XMLRPC status, sensitive paths).
How to Run
# Produce a delta report comparing WaveN to WaveN+1
# Read wave outputs, compare per-target, classify findings
Quick Reference
Delta Categories
| Category | Label | Meaning | Example |
|---|---|---|---|
| NEW | ++ | Finding that didn't exist in any prior wave | Port 3306 (MySQL) now OPEN |
| REGRESSION | -- | Service that was accessible but is now blocked | XMLRPC 200 -> 405 (hardened) |
| PERSISTENT | == | Vulnerability unchanged across all waves | CORS still reflecting since wave6 |
| CHANGE | ~ | Configuration changed but not a regression | WP users: 10 in wave7, 9 in wave9 |
| REVERSED | -> | A regression that was later undone (mitigation removed) | XMLRPC 405 (W9) -> 200 active (W10) |
REVERSED — Special Category
Reversed findings are regressions that later reverted to the original vulnerable state. This happens when:
- A WAF rule was applied temporarily then removed (common on GoDaddy/Cloudflare shared hosting)
- A plugin security update was rolled back
- Infrastructure was redeployed without the hardening
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.
- 12d ago First seen · 114 lines · 21 tokens per session scan A ca94f1dc1b16
cross-wave-delta-analysis is a skill published in the GitHub repository uphiago/recon-skills (1,254 stars, last pushed 10d ago), licensed MIT. It adds 21 tokens to every session and 1,251 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 2026-08-30.
Other skills, from other repositories
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implementing-aws-config-rules-for-compliance
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implementing-aws-security-hub-compliance
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implementing-azure-defender-for-cloud
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