security-toolkit

Even-handed investigation of loaded, contested topics. Research & investigation skills for thinking-with-AI - investigation protocols (deep-investigation, cui-bono / "follow the money", screening a dev job or employer for hidden military/defense ties), text & source deconstruction, frame rotation, and iterative verification that escalates to a recursive adversarial dialectic (generate a claim's exact opposite and test it). The skepticism is symmetric - turned on the consensus, the contrarian take, the model's own bias, and its own conclusions; it assumes no villain in advance (POSIWID: judge a method by what it does, not what it claims). Ships two deliberately basic MCP servers - thin data-access layers, not analysis engines; the skills do the analysis: financial-mcp (stock price, history, company info and standard technical indicators via yfinance, with a local ticker cache) and transparency-mcp (keyless public data - US Congress bills/members/votes via GovTrack, World Bank development indicators, and US nonprofit Form 990 filings via ProPublica).

22 skills · 2 commands · 4 agents · 2 MCP servers · hooks

A working proof of concept for catching the same structure in places that have nothing to do with each other - and in your own working process: notice such a regularity, capture it, and test each for a real shared mechanism, not surface resemblance. Today it's a growing, hand-kept list of specific observations that resurface when the shape shows up again, each accumulating a count of the times it has recurred. The self-organizing learner the system is built toward is the genuine direction, not yet the state - an early, already-useful step toward it. Memory for forms, not just facts; two local MCP servers (relational-memory + a usage-weighted knowledge graph, experimental). The term "vasana" is grounded in the plugin's axioms.

10 skills · 1 command · 1 agent · 2 MCP servers · hooks

Discipline for prompting and co-authoring with AI - nothing to configure, just skills. intrinsic-prompt-design: give the model the reason behind a rule, not just the rule; the reasons part clearly helps, even paired with plain imperatives, though so far only anecdotally (rigorous testing is still worth doing), and its bolder idea - deliberately leaving space for the model's own agency to fill - is the core experimental proposition. system-pilot: engineering discipline for deterministic systems, adapting the original Universal CLAUDE.md Protocol. skill-activation-testing: a two-tier A/B (cheap proxy + live firing test) for whether a description change actually fires, with the validity limit of each tier named, plus a stdlib scorer over claude plugin eval that adds case-level intervals, paired arm deltas and a pre-registered ship rule.

3 skills · 2 agents