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/samugit83/redamon/add-partial-reconnpx skills add samugit83/redamon --skill add-partial-recongit clone --depth 1 https://github.com/samugit83/redamonWrote 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/samugit83/redamon/add-partial-recon)<a href="https://agentmods.dev/skills/samugit83/redamon/add-partial-recon"><img src="https://agentmods.dev/badge/skills/samugit83/redamon/add-partial-recon.svg" alt="Measured on agentmods" 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 | $0.00103 | $0.00763 |
| Opus 5 | $0.00051 | $0.00381 |
| Sonnet 5 | $0.00021 | $0.00153 |
| Haiku 4.5 | $0.00010 | $0.00076 |
Grade A, and why
add-partial-recon 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 4d 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 — 71 lines — stays where its author put it; the contents beside it link to each section on GitHub.
When to Use
- Making an existing recon tool runnable as a single on-demand phase from the graph.
For adding the tool to the full pipeline, use recon-tool-integration. For the
graph write itself, use graph-db-writes. This skill is the partial-recon path:
graph-sourced inputs, the modal, and the single-phase re-run.
Critical Rules
- NEVER let partial-recon results create duplicate nodes. Partial runs merge
into the existing graph and must dedup via
MERGEon the tenant triple - seegraph-db-writes. Partial and full share the same graph. - NEVER expose a graph-only input type as a manual textarea.
SECTION_INPUT_MAPin nodeMapping.ts lists what the tool reads from the graph, but only the types that make sense for manual entry get a user field. Types likePortandEndpointcome from the graph only and must not be hand-entered. - ALWAYS wire the shared entry so it works in BOTH the full pipeline AND partial
recon. Partial recon is spawned as a separate container from the full
pipeline (
recon_orchestrator/container_manager.py); hook the shared entry function once so both inherit (seerecon-ai-enrichmentfor the same rule). - ALWAYS mirror the reference impl matching your tool's input shape, not an
arbitrary one: Naabu (
Subdomain+IP), Masscan (IPonly), Nmap (IP+Port), Katana (URL). The input-node shape drives the whole wiring.
Input-node shape -> reference impl
| Tool reads | User enters | Mirror |
|---|---|---|
| Subdomain + IP | Subdomain + IP (two textareas) | Naabu |
| IP only | IP (one textarea) | Masscan |
| IP + Port | IP (Port from graph) | Nmap |
| BaseURL | URL (maps to a BaseURL node) | Katana |
Commands
# recon/*.py is spawned fresh per job (volume-mounted) - no rebuild
./redamon.sh test unit # recon + root-recon sections
Resources
- docs/readmes/coding_agent_prompts/PROMPT.ADD_PARTIAL_RECON.md - full walkthrough, modal UI, input validation, reference impls
- Related skills:
recon-tool-integration,graph-db-writes,recon-ai-enrichment
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.
- 4d ago First seen · 71 lines · 103 tokens per session scan A 91b1a9b14280
add-partial-recon is a skill published in the GitHub repository samugit83/redamon (2,380 stars, last pushed yesterday), licensed MIT. It adds 103 tokens to every session and 763 once invoked, about $0.0005 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
workflow-orchestrator
Module Loop and Iteration Skill for orchestrating multi-phase penetration testing workflows. Use when coordinating sequential tool execution, managing dependencies between reconnaissance and vulnerability scanning modules, implementing adaptive fallback strategies, or managing workflow state across iterations.…
poc-validator
Proof-of-Concept (PoC) Validation Skill for security exploit verification. Use when validating exploitability of vulnerabilities, generating tailored payloads, executing exploits in sandboxed environments, or verifying successful exploitation (e.g., SQL injection, CVE exploitation, command injection). Triggers on…
Reconnaissance & OSINT Automation
Passive and active reconnaissance, subdomain enumeration, DNS analysis, technology fingerprinting, and OSINT data correlation for authorized security assessments.
research-orchestrator
Parallel research with 4 specialized agents (Official, Practical, Edge Cases, Future).
tdd-agent
Autonomous test-driven development agent that writes code to make tests pass.
kali-pentest
Execute authorized penetration testing via Kali Linux CLI tools over SSH or Docker. Covers: information gathering, vulnerability analysis, sniffing & spoofing, web/API testing, exploitation, password attacks, wireless, cloud-native security, RFID/NFC, VoIP/ICS, reverse engineering, forensics, post-exploitation/C2, and…