plan-engagement

plan-engagement is a skill for Claude Code from kalpmodi/akira. It costs 74 tokens per session (4,947 once invoked), scanned B, original, MIT.

A planning guide for starting a penetration test, which is an authorized security assessment of a website, server, or other target. It builds an attack plan from the target details and previously recorded security knowledge.

In plain words
What is it for?
It helps prepare bug-bounty work and other authorized security assessments of domains or IP addresses.
Why use it?
It gives the assessment a defined starting point and helps organize possible attack paths before testing begins.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: reads .claude/ paths.

Part of the akira plugin — 16 skills shipped together

Good fit It helps prepare bug-bounty work and other authorized security assessments of domains or IP addresses.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/kalpmodi/akira/plan-engagement
Install

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.

Any agent
npx skills add kalpmodi/akira --skill plan-engagement
Clone the repo
git clone --depth 1 https://github.com/kalpmodi/akira

Made for: Claude Code.

Or install akira, the plugin that ships this one along with the rest of its 16 skills.

Wrote 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.

agentmods badge for plan-engagement

README.md
[![agentmods](https://agentmods.dev/badge/skills/kalpmodi/akira/plan-engagement/github.svg)](https://agentmods.dev/skills/kalpmodi/akira/plan-engagement)
Your own site
<a href="https://agentmods.dev/skills/kalpmodi/akira/plan-engagement"><img src="https://agentmods.dev/badge/skills/kalpmodi/akira/plan-engagement/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.

agentmods 80×15 button for plan-engagement

Your own site · 80×15
<a href="https://agentmods.dev/skills/kalpmodi/akira/plan-engagement"><img src="https://agentmods.dev/badge/skills/kalpmodi/akira/plan-engagement.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 74 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,947 The whole file, excluding the scripts and references it only reads on demand.
Security scan B 1 finding. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00074 $0.04947
Opus 5 $0.00037 $0.02474
Sonnet 5 $0.00015 $0.00989
Haiku 4.5 $0.00007 $0.00495

Measured 10d ago against content hash 18bf90fbcfad, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade B, and why

plan-engagement scanned grade B with 1 finding 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 10d 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.

Cloud metadata endpointmediumServer-side request forgery

One request to 169.254.169.254 can return temporary IAM credentials.

→ add 169.254.169.254 to SSRF target list

Downgraded: this mod is about security review, or the phrase is quoted, so it is likely naming the pattern rather than instructing it.

skills/plan-engagement/SKILL.md · 505 lines

How it starts

The opening of the file, as written. The whole thing — 505 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Plan Engagement — Attack Graph Engine

Philosophy

You are not filling out a form. You are an attack planner initializing a live intelligence system.

Extract everything from the user's message. Ask at most one question — only if the target itself is completely missing. Everything else has smart defaults. Your job is to generate a dynamic attack graph, not a static checklist, and hand the user a running start.


Step 0: Bootstrap from Cross-Engagement Memory

Before anything else, read ~/.akira/memory.json to seed this engagement with prior intelligence.

MEMORY=~/.akira/memory.json

# Read global SCL counter for this session
SCL_COUNTER=$(jq -r '.scl_id_counter // 1' $MEMORY 2>/dev/null || echo 1)

# Read ATW flagged techniques (hallucination guard)
FLAGGED=$(jq -r '.hallucination_guard | to_entries[] | select(.value.flagged==true) | .key' $MEMORY 2>/dev/null)

# Read DNA registry for pattern matching
DNA_REGISTRY=$(jq -r '.dna_registry' $MEMORY 2>/dev/null)

echo "Memory loaded. SCL counter: $SCL_COUNTER | Flagged techniques: $(echo $FLAGGED | wc -w)"

If ~/.akira/memory.json does not exist:

mkdir -p ~/.akira
# Write initial memory.json with defaults - see references/memory-schema.md
# Set scl_id_counter to 1

Use memory to calibrate hypothesis priors in Step 2:

  • Match extracted tech hints against tech_vuln_priors keys
  • For each match, use stored prior_probability as the hypothesis starting point
  • Do NOT exceed 0.85 even if memory says higher (anti-overfitting cap)
  • Write flagged_techniques from hallucination_guard into session.json scalpel.doom_loop

Step 1: Infer From the Message

Extract without asking:

Extract Source Default if missing
Target domain, IP, URL, app name in message ask — only this
Program type "bug bounty", "pentest", "CTF", "my lab" bug_bounty
Platform "HackerOne", "Bugcrowd", "Intigriti" unknown
Tech hints AWS, OAuth, GraphQL, checkout, LDAP none
Constraint hints "no active scan", "stealth", "out of scope" none
Attack surface hints "403s", "login page", "API", "internal" none

Read the full file on GitHub · 505 lines

Files

What ships with it

4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 10d ago First seen · 505 lines · 74 tokens per session scan B 18bf90fbcfad

Subscribe to this mod's changes

plan-engagement is a skill published in the GitHub repository kalpmodi/akira (21 stars, last pushed 1mo ago), licensed MIT. It adds 74 tokens to every session and 4,947 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it B with 1 finding (cloud metadata endpoint). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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