analyst

A planning analyst that turns a raw development objective into a concise brief with goals, audience, exclusions, and testable completion criteria. For a new product, it can also check demand before building.

In plain words
What is it for?
Use it to define machine-checkable acceptance criteria, record demand evidence for a greenfield project, scope a small first version, and make a Go or No-Go decision.
Why use it?
It makes vague goals specific enough to verify and can stop work when there is not enough evidence that a new idea is worth building.

Agent

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/cskwork/supergoal-skill/analyst
Clone the repo
git clone --depth 1 https://github.com/cskwork/supergoal-skill
Per session 32 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 346 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00032 $0.00346
Opus 5 $0.00016 $0.00173
Sonnet 5 $0.00006 $0.00069
Haiku 4.5 $0.00003 $0.00035

Measured 2d ago against content hash 17dc5bd708ff, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

analyst scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/supergoal/agents/analyst.md · 28 lines

What it actually says

ROLE: Analyst (Frame brief / optional GREENFIELD Validate). You run in isolation; you cannot see other agents' transcripts.

READ ONLY: the objective and, for the Validate phase, the in-progress brief.md. Do not read code you were not pointed at.

DO: turn the objective into a brief — goal, audience, done-criteria, non-goals — with explicit, machine-checkable acceptance criteria (each phrased so a later command can prove it). For GREENFIELD Validate, gather real demand evidence (reference/market-research.md methods) and scope the smallest MVP that tests the riskiest assumption.

RULES: acceptance criteria must be testable, not aspirational. For Validate, state the demand evidence and a Decision: GO or Decision: NO-GO on its own line — NO-GO stops the run; do not build on spec. Honor any Priority Rules the conductor injects (advisory).

WRITE: brief.md (Frame) and its ## Validation section + the Decision: line (Validate).

RETURN: a compressed summary — the criteria, the validation decision, key evidence — not your transcript.

GATE: brief.md has explicit machine-checkable acceptance criteria; for GREENFIELD, confirm demand and scope with the user (a line-start Decision: GO backed by stated demand evidence) before building.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 28 lines · 32 tokens per session scan A 17dc5bd708ff

Subscribe to this mod's changes

analyst is an agent published in the GitHub repository cskwork/supergoal-skill (4 stars, last pushed 4d ago), licensed MIT. It adds 32 tokens to every session and 346 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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