TechNickAI
UserReusable procedures that make your AI handle recurring work the same good way every time. Paste one prompt; it recommends a few relevant skills and installs only what you approve. Works with Claude and Hermes.
Categories
Indexed Skills (35)
deep-dive
Use when told "do a deep dive", "go figure this out", or "don't reinvent the wheel" - researches a question across every relevant source and returns a decision. Also fires on "see what everyone else is doing", "use all the skills you have", "what's the best way to X", "should we build this or buy it", "is this possible", "what is everyone doing about X", "research this properly", and any consequential question handed over for a researched answer rather than a quick one. Routes one question across the relevant source classes (primary docs and source code, open-source repos, commercial vendors, practitioner community, academic work, prediction markets, and the operator's own prior work), verifies decision-critical claims against the PING failure modes, and returns a decision-first brief, with an explicit build-vs-adopt call when the question is a sourcing decision. Starts at the cheapest route that can settle the question and escalates only against a named gap.
grok-search
On-demand real-time web and X (Twitter) search via xAI's Grok. Reach for this when the user explicitly wants Grok to search, or asks for real-time / breaking / X-Twitter-native results that a general web search misses. Not the default web search — a named tool you invoke deliberately.
keep-going
Use when the user says "/keep_going", "keep going", or "continue" after the agent has stopped short — asked "which option?", narrated a plan instead of executing it, or claimed a blocker that is not real — while the user has already given clear direction. Also use proactively when the agent notices it is about to hand a solvable problem back instead of completing the work. Re-anchor on the ORIGINAL request, pick a decisive default, and chain actions until the work is verifiably done, stopping only for a blocker it can prove. Use when the user says "keep going", "continue", "you got stuck, unstuck yourself", "why did you stop", or runs the /keep_going slash command.
memory-cleanup
Use when a Hermes MEMORY.md or USER.md file is too large, bloated, stale, or over the recommended cap and you need to reduce prompt footprint without losing important facts. Applies a lossless memory diet: compress, relocate to SOUL.md/USER.md/AGENTS.md/context files, offload long-tail facts to the memory provider, convert reusable procedures into skills, then drop only stale or duplicate material. Includes dry-run, diff, and review gates before any write.
moa-solve
Use when you have a HARD, open-ended, high-stakes problem worth throwing multiple AI models at and pulling the best solution out — architecture decisions, strategy design, thorny debugging, research synthesis, "what am I missing", tool/system design. This is the SOLVE counterpart to multi-review (which critiques an existing artifact). It drives Hermes' NATIVE Mixture-of-Agents runtime (`/moa` and the `moa` virtual provider): a configured reference layer answers independently, then an aggregator writes a NEW best-of-breed answer via a component ledger — not an average, not a cut-and-paste splice. Also encodes WHEN NOT to use a panel (most problems), routing to a single strong model instead.
mob-check
Use when the user wants to know what real people are actually saying about a topic right now, not the SEO/editorial version. Pulls recent posts and engagement from Reddit, X, YouTube, Hacker News, Polymarket, GitHub, and the web, ranks by engagement and recency with a deterministic scorer, and writes one synthesized brief. Triggers: "what are people saying about X", "what's the vibe/sentiment on X", "X vs Y what does the community think", "how are people using X", "is X worth it", "latest on X", "take the pulse on X", "/mob-check", "what's the mob saying about X".
multi-review
Use when reviewing almost any meaningful artifact, decision, action, plan, code change, prompt, skill, research summary, outbound message, or public-facing content. Runs a small panel of diverse review lenses across model families when available, synthesizes findings into fix/ask/defer/wontfix decisions, and iterates until the result is ready.
project-steward
Run a portfolio of long-running projects as a chief of staff rather than a task runner. Use when you have several open-ended efforts that each need periodic attention, when scheduled agent runs are producing activity without progress, when a notification channel has become an unreadable wall of updates, or when you want an agent to direct specialist agents instead of doing their work. Covers the single-dispatcher pattern, reasoning out the single best move per project instead of picking from a fixed menu, spend gating on cluster health, and the living board that collapses a chat channel into one self-updating message. Triggers on "steward my projects", "the agent is busy but nothing is moving", "too many notifications to read", "stop it from redoing the specialist's work".
recall
Restore context from prior sessions, memories, and transcripts. Run /recall after /new to pick up where you left off, and also use when a bare-pronoun follow-up like "ship it", "do it", or "send that" likely points at a prior-session artifact. Designed to never dead-end — if one source has nothing, keep searching others until you have a useful picture.
report
File a report or piece of feedback from any Hermes platform session. Load this skill when the user says "/report", "file a bug", "report a bug", "something's broken", "something's wrong", "that's weird", "this is wrong", "this isn't working", "log this issue", or any other signal that they want to capture a problem for triage. Works on Telegram, Discord, Slack, and the CLI — the closed loop (a notification back to this chat when the issue is resolved) is wired automatically for gateway sessions.
robustify-doctor
Use when you need to know whether a Hermes agent is actually healthy — during a scheduled health check, after an outage or reboot, when someone asks "is X working?", or when an agent has gone quiet. Runs a deterministic collector that gathers facts across twelve subsystems, then reads those facts as an LLM to correlate symptoms into incidents, classify severity, and separate real breakage from things that merely look alarming. The script collects; the judgment is yours.
skill-librarian
Use when auditing an agent's skill library for broken runtime selection, ambiguous triggers, invalid metadata, oversized files, dangling links, role misfit, or duplicate skills. Audits the resolved enabled index and keeps all changes report-only until explicitly approved.
trust-framework
Use to govern your own autonomy, deciding when to act on your own versus ask for approval, and earning more freedom over time the way a new employee earns trust through training and repetition. Group your capabilities into skill buckets, classify every action as a reversible (two-way) or irreversible (one-way) door, hold a trust level per bucket (L1 supervised, L2 guardrailed, L3 autonomous), and keep an honest markdown ledger of your decisions that you read back to promote or demote yourself. Load when setting up your autonomy rules or when a consequential act-vs-ask decision comes up.
address-pr-comments
Use when a pull request has feedback from code-review bots (Cursor Bugbot, Codex, Claude Code Review, Greptile, CodeRabbit) or humans and you need to triage it, fix what is valid, push back on what is wrong, react and reply to every comment, and drive the PR to a clean, mergeable state. Trigger phrases: "address the PR comments", "handle the bot feedback", "get the review comments addressed".
diagram-rendering
Use when a fast hosted-render path is needed to turn D2, Mermaid, Graphviz, or Chart.js text into an inline-ready PNG for chat (Telegram, Discord, Slack) or a saved image. Handles the hosted-render + local-rasterize plumbing and platform gotchas (snap-chromium sandbox, D2-is-SVG-only, blank-render detection, transient host retries) so any fleet agent gets a clean picture on the first try. Prefer excalidraw for hand-drawn whiteboards and architecture-diagram for offline, pixel-controlled dark SVG cards; do not send sensitive content to public render hosts.
mini-app
Use when adding, removing, password-protecting, or troubleshooting a mini-app served by the hermes-config mini-app router (Caddy + PM2 + auth sidecar + Tailscale Serve/Funnel) on a fleet machine. Covers install, the Caddy route pattern, the auth sidecar conventions, exposing apps publicly via Funnel, Hermes dashboards behind a password, and the recurring pitfalls (Tailscale "serve reset" wars, the PM2 $HOME trap, funnel-eligible ports, strip-prefix requirements).
pr-review-sweep
Nightly sweep of recently-merged PRs to address unhandled review comments via a Claude Code sub-agent.
email-steward
Use when triaging one or more email inboxes on a schedule, removing obvious debris, quarantining promotional mail, and surfacing only messages that need the user's attention. Provides a Hermes-native workflow using cron, per-message sub-agent isolation, deterministic header heuristics, account adapters, visible Markdown state, reversible actions, and silent no-op runs.
google-docs
Use when creating, importing, formatting, editing, exporting, or quality-checking Google Docs from agent-generated markdown or local files.
google-sheets
Use when creating, populating, formatting, importing, exporting, or quality-checking Google Sheets from CSV, JSON arrays, or computed tabular data.
google-slides
Use when creating, importing, exporting, or quality-checking Google Slides decks via markdown-to-PPTX conversion and Drive import.
imessage-bluebubbles
Use when sending, reading, or searching iMessages from an agent on macOS, or when setting up, hardening, or debugging the BlueBubbles iMessage bridge. Also use when an existing chat.db/imsg approach breaks with permissionDenied, "authorization denied (code 23)", or hangs with no output after a macOS or Python upgrade.
vapi-calls
Place and manage real outbound phone calls through the Vapi voice AI platform. Use when an agent needs to reach a human by phone — a reminder, a confirmation, a question for a business, an appointment booking, or any errand that a voice conversation handles better than a message. Covers first-time setup, per-call configuration, live call control, and reading the result afterward.
data-verification
Use when data will drive a decision: is it profitable, did X cause Y, which cohort wins. Load BEFORE reporting any number, rate, P&L, backtest result, metrics review, cost model, funnel, or A/B outcome. Five questions that catch the errors re-checking arithmetic never catches, because the calculation is usually right and the input or the question is wrong.
check-upstream-first
Use before debugging a framework or dependency bug from its source, and before writing any local patch. Establishes which install and version is actually running, then searches the project's issue tracker and release notes for an existing fix. Prevents the common waste of hand-patching a source tree that nothing executes, or shipping a fix for a bug that was resolved weeks ago.
delegation-handoff
Use when handing work to a background agent or subprocess, or when one comes back reporting success. Covers verifying the premise before dispatch, writing a brief the worker can finish inside its budget, and checking the artifact yourself afterward. Prevents acting on a self-reported success, since a worker claiming "uploaded" or "file written" is a claim, not evidence.
is-it-really-broken
Use when a health check, audit, or monitor says something is BROKEN, before repeating that to anyone. Re-runs the check from the same context the failure came from and separates real failure from unknown, since a timeout, an HTTP 000, or a permission error means the test could not answer — not that the thing is down. Prevents reporting an outage that is actually a broken probe.
prove-the-setting-works
Use when about to tell someone a config change will (or will not) do what they want — hide a UI element, disable a provider, silence a channel, pin a new model version. Copies the config to a throwaway profile, changes one setting, re-runs the real code path, and reads the actual output. Prevents promising a fix that silently does nothing, and prevents calling something impossible when a different setting would have worked.
find-the-real-bottleneck
Use when something in a multi-layer stack is slow, memory-hungry, or expensive and you need to prove WHERE the cost actually originates before recommending a fix — a slow dashboard fronting a busy proxy, a request path spanning client → gateway → router → upstream API, a process whose RSS keeps climbing, a spend spike whose obvious explanation doesn't survive arithmetic. Enforces measuring each arrow in a causal chain rather than asserting a plausible mechanism, gives cheap discriminating tests (CPU-vs-wall, component-in-isolation, do-nothing probe, bypass test, sample-over-time), separates a failing subsystem that is the CAUSE from a downstream SYMPTOM, and refuses to call a fault "flake" before counting recurrence and comparing sibling hosts by version. Load before answering "why is X slow", "is it the database", "is DNS/the network bringing this box down", "was that just flake", or when about to blame GC, cache, table size, or RAM for a latency problem.
live-database-maintenance
Use when cleaning up, compacting, backing up, or restoring a SQLite database that a running service still holds open, or when one reports "database disk image is malformed". Covers measuring compaction cost before taking a lock, distinguishing a torn copy from real corruption, locating which table is damaged, and designing a retention policy. Prevents a maintenance window that takes down live traffic, and prevents a health check that reports ok on a broken file.
scheduled-job-runner
Use when a scheduled job silently does nothing, reports success after failing, or needs to move onto a common runner. Ships a tested execution adapter that pins the interpreter, enforces timeouts, records every run with a real exit code, and locks its ledger. Prevents the failure where cron picks an interpreter by file extension and the job dies on a missing import nobody sees.
stop-the-noise
Use when something is sending repeated, unwanted, or unread messages — a scheduled job that reports every run, a webhook firing once per event, progress commentary nobody asked for. Finds which source is actually producing the messages and silences it without muting real alerts. Prevents the two usual mistakes: counting duplicates while still delivering them, and muting the channel that carried the one message that mattered.
upgrade-a-live-service-safely
Use when upgrading, rebuilding, or redeploying a service that is CURRENTLY SERVING production traffic — an LLM router, API gateway, web app, or any long-running daemon on a host you reach over SSH. Covers the build-in-place trap (build tooling that deletes the running service's working directory), CPU saturation starving both the service and sshd, detaching builds so an SSH pipe drop can't kill them mid-write, the release-dir + symlink swap pattern that makes rollback atomic, out-of-band health probing when you can no longer reach the box, and cloud-level reboot recovery. Also covers offloading the build to CI entirely (free arm64 GitHub runners), right-sizing a host by comparing runtime RSS against build peak, and smoke-testing a new release on a test port against a copy of the DB before swapping. Load this BEFORE running any build or install command on a host that is answering live requests.
writing-for-non-engineers
Use when writing a plan, status report, incident summary, or recommendation for someone who does not work in the system being described. Leads with what changed for them, keeps the technical detail underneath, and gives them at most one real decision to make. Prevents the two failures that lose a non-technical reader: a wall of internals, and a list of options with no recommendation.
fieldy
Use when reading conversations, transcripts, summaries, or action items captured by a Fieldy AI wearable note taker, or when the user mentions Fieldy, their wearable, or wants the record of something said in person rather than on a video call. Covers API key setup, the time-window query model, pagination, and the async-processing and speaker-labelling gotchas that make naive reads report incomplete data.
Bio shown is the top-scored skill's repo description as a fallback — real GitHub bios land in a future update.