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SkillsMP has collected 61 skills from peterbamuhigire/digital-research-skills. Open a skill to review its source and details.
Showing 40 of 61 collected skills.
Use when routing evidence-disciplined research across intake, source evaluation, web search, OSINT, due diligence, academic review, policy research, synthesis, verification, and final deliverables.
Use when research requires quantitative modelling: market sizing, triangulation, sensitivity analysis, scenario models, assumption registers, forecast models, data-quality caveats, and model audit checks.
Use when admitting any source into research and assessing its provenance, authority, independence, timeliness, bias, media integrity, and fit for a claim; use source-verification afterward to test URLs, quotes, statistics, claim links, and release readiness.
Use when drafting or revising an academic paper, essay, thesis, or dissertation with source-away composition, originality, citation, synthesis, voice, and register controls; use academic-reporting-standards for selecting formal study-reporting rules.
Use when planning, drafting, reviewing, or formatting a dissertation from research question through defence-ready manuscript; use academic-writing for prose originality and research-design for method selection.
Use when the engine must turn research into reusable knowledge assets, audience-specific variants, and monetizable offerings rather than a one-off document only. Encodes knowledge audit, asset design, reuse discipline, and commercialization framing.
Use when a research project needs formal questions, method selection, case logic, historical or trend design, MROC design, knowledge-lifecycle modelling, or a research-design document; use research-orchestration for wave planning and research-techniques for a…
Use when producing or revising any research artefact to prevent generic, unsupported, repetitive, or mechanically styled output in real time; use ai-slop-audit to grade a concrete completed iteration independently.
Use when drafting or revising non-academic prose such as emails, memos, letters, plans, articles, web copy, speeches, resumes, or executive briefs; use academic-writing for scholarly outputs and executive-communication for decision-led executive synthesis.
Use when starting or replanning a multi-source research project that needs a research-type choice, discipline strategy, reading mode, wave plan, verification, gap filling, and synthesis; use research-design for formal method design and research-techniques for…
Use when a research project must verify sources, URLs, quotes, statistics, claim-source links, archive snapshots, registry completeness, and release readiness after source evaluation and before synthesis or publication.
Use when starting a scaffolded research workspace that needs an explicit project profile, methodology, audience-output matrix, wave roadmap, and dispatch gate; do not use for routine work inside an already initialised project.
Use when an academic paper, thesis, dissertation, journal article, systematic review, or examinable artefact must follow a named reporting or examination standard; use academic-writing instead for prose craft without a reporting-standard decision.
Use when a forward-looking judgment or contested-evidence question needs structured analytic techniques, bias checks, sourcing discipline, alternatives, and calibrated estimative language; use critical-reasoning-and-argument for general claim and warrant…
Use when lawful public-source investigation needs stakeholder reconnaissance, adverse-media review, chronology, source capture, or case-vault discipline; use pi-investigation only for authorised licensed-PI work and refuse surveillance, harassment, stalking,…
Use when a research project needs a specific named technique — mini-analysis, crosswalk matrix, cross-cohort synthesis, gap analysis, reference interview, controlled vocabulary, pain-point taxonomy, search-operator grammar, Google-search API. Companion to…
Use when research must become a traceable evidence-to-claim knowledge graph rather than loose notes. Encodes source, evidence, claim, warrant, inference, synthesis, gap, contradiction, and finding nodes with registry-ready relationships.
Use when designing, running, or auditing multi-agent research operations: wave planning, task briefs, agent roles, tool boundaries, verification loops, failure recovery, evaluation, and portable runtime behavior across Codex, Claude, and other agents.
Use when designing evaluation, failure analysis, feedback capture, regression datasets, synthetic data controls, and data flywheels for AI-assisted research and agentic workflows.
Use when auditing a concrete artefact for AI slop after a major iteration or before release, with evidence-backed findings, fixes, genericness score, and A/B/C/F verdict; use anti-ai-slop during production rather than for retrospective grading.
Use when selecting or designing the exact shape of a decision-grade analytical artifact: intelligence brief, estimative memo, warning note, decision memo, status report, evaluation report, research report, due-diligence memo, market analysis, or executive…
Use when research output makes forecasts, probability judgments, risk calls, market outlooks, scenario likelihoods, warning indicators, or confidence claims that must be calibrated, scored, updated, and separated from source reliability.
Use when starting a new project, scoping a feature, or deciding which skill stack to load — provides the canonical Foundation → Implementation → Validation → Companions skill set per technology domain. The lookup table that turns "I'm building X" into "load…
Use when the engine's research must be turned into consulting-grade problem solving: issue trees, hypothesis-led workplans, analysis plans, stakeholder management, implementation logic, and transformation framing. Encodes consulting craft without relaxing…
Use when an output makes claims, explanations, interpretations, judgments, recommendations, forecasts, or persuasive conclusions that need explicit warrants, assumptions, countercases, and implications; use analytic-tradecraft for estimative or…
Use when profiling, cleaning, merging, or validating tabular research data through encoding, tidy-structure, anomaly, lineage, and quality gates; use dataset-discovery-and-analysis first when the dataset still needs to be found or retrieved.
Use whenever a research project would benefit from public datasets — finds them across government / IGO / academic / ML hubs, retrieves with integrity checks, and produces a Segnini-style five-step quality profile (completeness, duplicates, accuracy,…
Use when research must support a decision, recommendation, investment, policy choice, product bet, go/no-go call, prioritization, or executive memo. Encodes decision framing, alternatives, values, uncertainty, tradeoffs, pre-mortem, and commitment quality…
Use when generating or revising a project's triple-layer AGENTS.md documentation from observed workspace structure, technology, data, and planning evidence; do not use for general technical documentation or a single ad hoc README edit.
Use when defining or auditing the mandatory operating sequence for the research engine: evidence discipline, research design, collection, verification, reasoning, tradecraft, calibration, decision support, report shape, productization, and export.
Use when conducting lawful corporate, financial, sanctions, regulatory, ownership, or background-check due diligence that needs an auditable finding trail and CARA resolution; use osint-investigation for broader open-source inquiry without a diligence…
Use when English content must sound natural and professional for East African readers; apply British-influenced regional usage after the content-owning skill, but route translation or substantive content strategy elsewhere.
Use when creating, importing, repairing, or validating Excel workbooks with formulas, tables, charts, controls, and professional formatting; use python-document-generation for multi-format application exports.
Use when verified research must become an answer-first memo, report, deck, or one-pager for senior readers; this skill structures the argument and page messages, while critical-reasoning-and-argument tests the underlying claims.
Use when an academic proposal, thesis, dissertation, project, defence, or research-governance artefact must be checked against a named Kenya-based handbook; use primary-research for fieldwork design and source-evaluation for evidence quality.
Use when turning a corpus into reusable, monetizable, verifiable knowledge assets: entity-event-issue extraction, claim libraries, evidence maps, reusable briefs, ontology seeds, dossiers, and refresh cadences.
Use when creating or updating an end-user manual or reference guide for an ERP or SaaS feature; use project-requirements for product scope and professional-word-output for final DOCX production.
Use when Markdown files need mechanical lint repair for headings, list spacing, fences, and whitespace without changing meaning; use a writing or editing skill when prose or structure needs substantive revision.
Use when a verified corpus or brief must be compressed into a navigable mind map for synthesis, taxonomy, wave planning, or decomposition; use cross-cohort-synthesis for final comparative findings and knowledge-mining for reusable claim assets.
Use when a question turns on statutes, regulations, cases, treaties, legal authority, or jurisdiction-specific analysis; use source-evaluation for general source quality and refuse to treat unverified currency or secondary commentary as controlling law.