mcpbeat Sign in

Engagement Memory Skill for Claude

Use when recalling prior techniques at recon/weaponize, or recording a confirmed finding at report — cross-engagement pattern memory ranked by impact

12k tokens
context cost
the whole folder, loaded on every use
4
files
ships runnable scripts
0
copies elsewhere
how many repositories repackaged it
334
stars on the repo
on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/hypnguyen1209/offensive-claude --skill engagement-memory

What comes with it

43 292 bytes besides the instruction
scripts/pattern_db.py
scripts/rotation.py
scripts/schemas.py

The instruction itself

6 sections, as written by the author

Engagement Memory (cross-engagement learning)

When to Activate

  • At recon/weaponize: recall what already worked against this target class / tech stack.
  • At report: persist each [CONFIRMED] finding as a reusable pattern (ranked by impact).
  • Periodic housekeeping: compact the pattern DB / rotate the audit log.

Model

Append-only JSONL store (~/.claude/engagement-memory/patterns.jsonl, override $ENGAGEMENT_DB).

Three record types in their own files so they never mix: patterns (patterns.jsonl),

target profiles (profiles.jsonl), audit log (audit.jsonl, disposable). A pattern is keyed

by (target, vuln_class, technique), ranked by severity / CVSS / confidence (real impact, never

payout), and carries a lifecycle status (proposed/active/stale/deprecated/...). Recall is an

explicit top-N query (anti-context-bloat). Duplicates merge (count bumped, most-recent status

wins), never blind-discarded; compact runs automatically over a size threshold and stays lossless.

TTL stale patterns and deprecated/rejected ones drop out of default recall but are kept.

Commands

# RECALL — relevance-ranked (stdlib BM25 + aliases), active-only by default
python skills/engagement-memory/scripts/pattern_db.py match --vuln-class ssrf --query "imds metadata" --tech-stack aws
# INJECT — budgeted prior-intel card for a phase (top-N, byte-capped; $ENGAGEMENT_MEMORY_MODE=auto|debug|off)
python skills/engagement-memory/scripts/pattern_db.py inject --vuln-class ssrf --query imds --max-bytes 1500

# RECORD a confirmed finding (flags or finding JSON). A key collision needs --resolve update|merge|reject|force.
python skills/engagement-memory/scripts/pattern_db.py record --target acme.com --vuln-class ssrf \
    --cwe CWE-918 --attack-id T1190 --severity high --cvss 9.1 --tech-stack nginx,aws --technique "metadata theft"
python skills/engagement-memory/scripts/pattern_db.py record --json '<finding json from validate_findings>'

# LIFECYCLE + cross-client
python skills/engagement-memory/scripts/pattern_db.py promote   --target acme.com --vuln-class ssrf --technique "metadata theft" [--global]
python skills/engagement-memory/scripts/pattern_db.py deprecate --target acme.com --vuln-class ssrf --technique "metadata theft"
python skills/engagement-memory/scripts/pattern_db.py match --vuln-class ssrf --include-global   # add sanitized cross-client TTPs

# PROFILES + housekeeping + observability
python skills/engagement-memory/scripts/pattern_db.py profile --target acme.com --tech-stack nginx,aws --endpoints /api,/admin
python skills/engagement-memory/scripts/pattern_db.py recall-profile --target acme.com
python skills/engagement-memory/scripts/pattern_db.py compact         # manual lossless dedup-merge
python skills/engagement-memory/scripts/pattern_db.py stats           # patterns by class + profile count
python skills/engagement-memory/scripts/pattern_db.py audit-stats     # action log: by tool/action/outcome

Or use the /engage.memory command (recall | inject | record | promote | deprecate | gc | stats).

OPSEC & Detection

| Concern | Note |

|---------|------|

| Secrets at rest | Stores technique + CWE/CVSS + an evidence *reference*, never loot. A secret-input guard rejects evidence_ref/source that look like inline secrets (private keys, password=, AKIA, JWTs, tokens) — store a path; rotate the exposed credential, don't just delete. |

| Cross-client bleed | Per-client isolation is the default ($ENGAGEMENT_DB). The shared global store is opt-in (promote --global / record --global) and sanitized (target + evidence blanked); recall it only with --include-global. |

| Trust | New auto-captures can be proposed; only confirmed/reviewed findings are active. A key collision is review-gated (--resolve), not silently merged. |

| Auditability | Every record/match/compact/promote — and every refused line (denial) — is written to audit.jsonl (rotated by discard, with a retention-gap marker). The append-only patterns journal + audit log ARE the history. |

| Integrity | Records carry schema_version; malformed/type-poisoned/foreign lines are skipped on read, never trusted. |

Deep Dives

  • scripts/schemas.py — record types (pattern/audit/target_profile/retention_gap), validation + secret guard, pattern_key/pattern_id, impact+confidence rank_score, recency-resolving merge.
  • scripts/pattern_db.py — typed routing, merge-on-read with TTL staleness, BM25 relevance recall, inject, lifecycle verbs, global scope, CLI.
  • scripts/rotation.pycompact/maybe_gc (lossless dedup-merge, auto-triggered) vs rotate_audit (discard the disposable log + write a retention-gap marker).

Other skills for the same job

different authors, same section of the catalogue
Protocolsio Integration
by christophacham
×4

Integration with protocols.io API for managing scientific protocols. This skill should be used when working with protocols.io to search, create, update, or publish protocols; manage protocol steps and materials; handle discussions and comments; organize workspaces; upload and manage files; or integrate protocols.io functionality into workflows. Applicable for protocol discovery, collaborative protocol development, experiment tracking, lab protocol management, and scientific documentation.

16k tokens
Tailored Resume Generator
by frostant
×4

Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances

3k tokens
Excalidraw Diagram Generator
by github
vendor ×3

Generate Excalidraw diagrams from natural language descriptions. Use when asked to "create a diagram", "make a flowchart", "visualize a process", "draw a system architecture", "create a mind map", or "generate an Excalidraw file". Supports flowcharts, relationship diagrams, mind maps, and system architecture diagrams. Outputs .excalidraw JSON files that can be opened directly in Excalidraw.

36k tokens scripts
Expo Dev Client
by openai
vendor ×3

Build and distribute Expo development clients locally or via TestFlight

961 tokens
Executing Plans
by ZhanlinCui
×3

Use when you have a written implementation plan to execute in a separate session with review checkpoints

542 tokens
Anndata
by christophacham
×3

Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.

16k tokens
Benchling Integration
by christophacham
×3

Benchling R&D platform integration. Access registry (DNA, proteins), inventory, ELN entries, workflows via API, build Benchling Apps, query Data Warehouse, for lab data management automation.

14k tokens
Biopython
by christophacham
×3

Comprehensive molecular biology toolkit. Use for sequence manipulation, file parsing (FASTA/GenBank/PDB), phylogenetics, and programmatic NCBI/PubMed access (Bio.Entrez). Best for batch processing, custom bioinformatics pipelines, BLAST automation. For quick lookups use gget; for multi-service integration use bioservices.

24k tokens

How to use it

Copy the folder

Take hypnguyen1209/engagement-memory from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.