Agent skill

Prismer Spike

by Prismer-AI in Prismer-AI/PrismerCloud

Throwaway experiments to validate an idea before build. An agent skill from Prismer-AI/PrismerCloud.

MITAuto-check passed

Install Prismer Spike

skills CLI
$ npx skills add Prismer-AI/PrismerCloud --skill prismer-spike -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Prismer-AI/PrismerCloud prismer-spike --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/Prismer-AI/PrismerCloud.git skills-src && mkdir -p .claude/skills && cp -r skills-src/sdk/cloud/catalog/skills/prismer-spike .claude/skills/prismer-spike && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
prismer-spike
GitHub stars
1.6k
Used in
4 other repos
Token cost
~2.4k tokens
SKILL.md length
1,058 words
Files
4
Skills in repo
88
Repo updated
First seen
Licence
MIT

At a glance

Throwaway experiments to validate an idea before build. An agent skill from Prismer-AI/PrismerCloud.

  • Works in 5 steps: Decompose → Align (for multi-spike ideas) → Research (per spike, before building) → …
  • SKILL.md covers Prismer execution contract, When NOT to use this, If the user has the full GSD… and Core method, plus 4 more sections
  • Calls python and npx; reaches websockets.readthedocs.io

What it does

Prismer Spike is an agent skill from Prismer-AI/PrismerCloud. Throwaway experiments to validate an idea before build.

Its SKILL.md is about 2.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files (for example `NOTICE.md`).

The licence is MIT.

Example prompts

  • “/prismer-spike”

Requirements

  • Python 3
  • Node.js
  • Docker

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Decompose
  2. Align (for multi-spike ideas)
  3. Research (per spike, before building)
  4. Build
  5. Verdict

What it can do on your machine

Read from SKILL.md and the folder at commit 0d240dd. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • python
    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • websockets.readthedocs.io

    Also links to:

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Prismer Spike loads about 2.4k tokens when it runs. Until then it costs about 17 tokens; SKILL.md has 1,058 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~17
When it runs · the whole SKILL.md, loaded when a task matches
~2.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Prismer-AI/PrismerCloud at commit 0d240dd, republished under its MIT licence (© Prismer-AI). 1,058 words, ~2,390 tokens.

Download SKILL.mdSave it as .claude/skills/prismer-spike/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
prismer-spike
description
Throwaway experiments to validate an idea before build.
scope
coding
version
1.0.0
author
Hermes Agent (adapted from gsd-build/get-shit-done)
license
MIT
platforms
linux, macos, windows
metadata.nativeReplaces
spike

Prismer execution contract

This is the uniquely named prismer-spike skill, adapted from Hermes. Use the actual tools exposed by the executing host; examples using terminal, process, delegate_task, vision_analyze or browser_* are not tool registrations. Missing dependencies do not hide this skill. Report command startup, version, account/permissions and task-specific live verification separately. Use task-owned artifact paths and existing user authorization; do not change shared accounts, Runtime/provider configuration, global security settings or unrelated work. See NOTICE.md and LICENSE for resource provenance. Runtime availability and upstream-entry suppression are owned by the integration layer.

Spike

Use this skill when the user wants to feel out an idea before committing to a real build — validating feasibility, comparing approaches, or surfacing unknowns that no amount of research will answer. Spikes are disposable by design. Throw them away once they've paid their debt.

Load this when the user says things like "let me try this", "I want to see if X works", "spike this out", "before I commit to Y", "quick prototype of Z", "is this even possible?", or "compare A vs B".

When NOT to use this

  • The answer is knowable from docs or reading code — just do research, don't build
  • The work is production path — use the plan skill instead
  • The idea is already validated — jump straight to implementation

If the user has the full GSD system installed

If gsd-spike shows up as a sibling skill (installed via npx get-shit-done-cc --hermes), prefer gsd-spike when the user wants the full GSD workflow: persistent .planning/spikes/ state, MANIFEST tracking across sessions, Given/When/Then verdict format, and commit patterns that integrate with the rest of GSD. This skill is the lightweight standalone version for users who don't have (or don't want) the full system.

Core method

Regardless of scale, every spike follows this loop:

decompose  →  research  →  build  →  verdict
   ↑__________________________________________↓
                  iterate on findings
1. Decompose

Break the user's idea into 2-5 independent feasibility questions. Each question is one spike. Present them as a table with Given/When/Then framing:

#SpikeValidates (Given/When/Then)Risk
001websocket-streamingGiven a WS connection, when LLM streams tokens, then client receives chunks < 100msHigh
002apdf-parse-pdfjsGiven a multi-page PDF, when parsed with pdfjs, then structured text is extractableMedium
002bpdf-parse-camelotGiven a multi-page PDF, when parsed with camelot, then structured text is extractableMedium

Spike types:

  • standard — one approach answering one question
  • comparison — same question, different approaches (shared number, letter suffix a/b/c)

Good spike questions: specific feasibility with observable output. Bad spike questions: too broad, no observable output, or just "read the docs about X".

Order by risk. The spike most likely to kill the idea runs first. No point prototyping the easy parts if the hard part doesn't work.

Skip decomposition only if the user already knows exactly what they want to spike and says so. Then take their idea as a single spike.

2. Align (for multi-spike ideas)

Present the spike table. Ask: "Build all in this order, or adjust?" Let the user drop, reorder, or re-frame before you write any code.

3. Research (per spike, before building)

Spikes are not research-free — you research enough to pick the right approach, then you build. Per spike:

  1. Brief it. 2-3 sentences: what this spike is, why it matters, key risk.

  2. Surface competing approaches if there's real choice:

    ApproachTool/LibraryProsConsStatus
    ............maintained / abandoned / beta
  3. Pick one. State why. If 2+ are credible, build quick variants within the spike.

  4. Skip research for pure logic with no external dependencies.

Use Hermes tools for the research step:

  • web_search("python websocket streaming libraries 2025") — find candidates
  • web_extract(urls=["https://websockets.readthedocs.io/..."]) — read the actual docs (returns markdown)
  • terminal("pip show websockets | grep Version") — check what's installed in the project's venv

For libraries without docs pages, clone and read their README.md / examples/ via read_file. Context7 MCP (if the user has it configured) is also a good source — mcp_*_resolve-library-id then mcp_*_query-docs.

Show full SKILL.md (428 more words)Show less
4. Build

One directory per spike. Keep it standalone.

spikes/
├── 001-websocket-streaming/
│   ├── README.md
│   └── main.py
├── 002a-pdf-parse-pdfjs/
│   ├── README.md
│   └── parse.js
└── 002b-pdf-parse-camelot/
    ├── README.md
    └── parse.py

Bias toward something the user can interact with. Spikes fail when the only output is a log line that says "it works." The user wants to feel the spike working. Default choices, in order of preference:

  1. A runnable CLI that takes input and prints observable output
  2. A minimal HTML page that demonstrates the behavior
  3. A small web server with one endpoint
  4. A unit test that exercises the question with recognizable assertions

Depth over speed. Never declare "it works" after one happy-path run. Test edge cases. Follow surprising findings. The verdict is only trustworthy when the investigation was honest.

Avoid unless the spike specifically requires it: complex package management, build tools/bundlers, Docker, env files, config systems. Hardcode only non-sensitive synthetic fixtures; never credentials or production endpoints — it's a spike.

Building one spike — a typical tool sequence:

terminal("mkdir -p spikes/001-websocket-streaming")
write_file("spikes/001-websocket-streaming/README.md", "# 001: websocket-streaming\n\n...")
write_file("spikes/001-websocket-streaming/main.py", "...")
terminal("cd spikes/001-websocket-streaming && python main.py")
# Observe output, iterate.

Parallel comparison spikes (002a / 002b) — delegate. When two approaches can run in parallel and both need real engineering (not 10-line prototypes), fan out with delegate_task:

delegate_task(tasks=[
    {"goal": "Build 002a-pdf-parse-pdfjs: ...", "toolsets": ["terminal", "file", "web"]},
    {"goal": "Build 002b-pdf-parse-camelot: ...", "toolsets": ["terminal", "file", "web"]},
])

Each subagent returns its own verdict; you write the head-to-head.

5. Verdict

Each spike's README.md closes with:

markdown
## Verdict: VALIDATED | PARTIAL | INVALIDATED

### What worked
- ...

### What didn't
- ...

### Surprises
- ...

### Recommendation for the real build
- ...

VALIDATED = the core question was answered yes, with evidence. PARTIAL = it works under constraints X, Y, Z — document them. INVALIDATED = doesn't work, for this reason. This is a successful spike.

Comparison spikes

When two approaches answer the same question (002a / 002b), build them back to back, then do a head-to-head comparison at the end:

markdown
## Head-to-head: pdfjs vs camelot

| Dimension | pdfjs (002a) | camelot (002b) |
|-----------|--------------|----------------|
| Extraction quality | 9/10 structured | 7/10 table-only |
| Setup complexity | npm install, 1 line | pip + ghostscript |
| Perf on 100-page PDF | 3s | 18s |
| Handles rotated text | no | yes |

**Winner:** pdfjs for our use case. Camelot if we need table-first extraction later.

Frontier mode (picking what to spike next)

If spikes already exist and the user says "what should I spike next?", walk the existing directories and look for:

  • Integration risks — two validated spikes that touch the same resource but were tested independently
  • Data handoffs — spike A's output was assumed compatible with spike B's input; never proven
  • Gaps in the vision — capabilities assumed but unproven
  • Alternative approaches — different angles for PARTIAL or INVALIDATED spikes

Propose 2-4 candidates as Given/When/Then when scope is unclear. Otherwise execute the user's already-authorized experiment without asking again.

Output

  • Create a unique task-owned scratch directory outside production source; do not overwrite an existing spikes/ tree
  • One dir per spike: NNN-descriptive-name/
  • README.md per spike captures question, approach, results, verdict
  • Keep the code throwaway — a spike that takes 2 days to "clean up for production" was a bad spike

Attribution

Adapted from the GSD (Get Shit Done) project's /gsd-spike workflow — MIT © 2025 Lex Christopherson (gsd-build/get-shit-done). The full GSD system offers persistent spike state, MANIFEST tracking, and integration with a broader spec-driven development pipeline. No global GSD installation is required or authorized by this skill.

© Prismer-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files in sdk/cloud/catalog/skills/prismer-spike of Prismer-AI/PrismerCloud.

  • SKILL.md
  • LICENSE
  • LICENSE.gsd
  • NOTICE.md

Open the folder on GitHubat commit 0d240dd

Used in 4 other repositories

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 4 other GitHub owners. This page covers the copy in Prismer-AI/PrismerCloud, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Prismer Spike next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Prismer Spike compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Prismer Spike this skillPrismer-AI/PrismerCloud1.6k4 repos~2.4kAutomated safety check: PassMIT
Spikeopenclaw/openclaw392k1 repos~473Automated safety check: PassMIT
Finding ExperimentsPostHog/posthog40k—~826Automated safety check: PassCustom licence
ExperimentsArize-ai/phoenix12k—~1.8kAutomated safety check: PassCustom licence
Scroll Experiencesickn33/agentic-awesome-skills47k2 repos~534Automated safety check: PassMIT
Idea Darwinsickn33/agentic-awesome-skills47k2 repos~1.1kAutomated safety check: PassMIT

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Questions about Prismer Spike

What does Prismer Spike do?

Throwaway experiments to validate an idea before build. An agent skill from Prismer-AI/PrismerCloud. Prismer Spike is an agent skill from Prismer-AI/PrismerCloud. Throwaway experiments to validate an idea before build.

How do I install Prismer Spike in Claude Code?

Run `npx skills add Prismer-AI/PrismerCloud --skill prismer-spike -a claude-code`. Or copy the skill folder (sdk/cloud/catalog/skills/prismer-spike in Prismer-AI/PrismerCloud) into .claude/skills/prismer-spike in your project. Claude Code loads it when a task matches its description.

How do I install Prismer Spike in Codex?

Run `npx skills add Prismer-AI/PrismerCloud --skill prismer-spike -a codex`. Or copy the skill folder (sdk/cloud/catalog/skills/prismer-spike in Prismer-AI/PrismerCloud) into .agents/skills/prismer-spike in your project. Codex loads it when a task matches its description.

Can I use Prismer Spike in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Prismer-AI/PrismerCloud --skill prismer-spike -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/prismer-spike, .gemini/skills/prismer-spike, .github/skills/prismer-spike and .opencode/skills/prismer-spike in your project.

What does Prismer Spike need to run?

Going by SKILL.md and its folder, Prismer Spike needs the command-line tools its instructions call (python and npx). Our summary lists: Python 3; Node.js; Docker.

Does Prismer Spike access the network?

SKILL.md names 2 domains. In commands or code: websockets.readthedocs.io; the agent is likely to contact it when it follows the instructions. As links in the text: github.com. This is read from the text; nothing was executed.

Is Prismer Spike safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Prismer Spike use?

Prismer Spike is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Prismer Spike use?

About 2.4k tokens (SKILL.md is roughly 9.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Prismer Spike?

Skills that share tags, products or a category with Prismer Spike: Spike (openclaw/openclaw, 392k stars), Finding Experiments (PostHog/posthog, 40k stars), Experiments (Arize-ai/phoenix, 12k stars) and Scroll Experience (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Prismer Spike?

Prismer-AI (a GitHub organization) maintains it in Prismer-AI/PrismerCloud, which has 1,555 GitHub stars. The repository holds 88 skills in this directory. The repository was last updated on October 11, 2026.

Source: Prismer-AI/PrismerCloud on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.