startup-interview-synthesis

startup-interview-synthesis is a skill for Claude Code from forjd/startup-ideation-skills. It costs 53 tokens per session (1,434 once invoked), scanned A, original, MIT.

A method for turning startup customer interviews, outreach replies, validation calls, and test results into an evidence-based decision. It distinguishes observed behavior and exact statements from opinions, compliments, guesses, and founder interpretation.

In plain words
What is it for?
Use it to organize interview evidence, classify signals by strength, examine the problem and buyer, compare evidence with success or kill criteria, and recommend whether to proceed, pause, or stop before defining a first product version.
Why use it?
It prevents polite interest from being mistaken for proof that a real problem or paying market exists. It also keeps contradictions visible so they can affect the decision.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the startup-ideation-skills plugin — 6 skills shipped together

Good fit Use it to organize interview evidence, classify signals by strength, examine the problem and buyer, compare evidence with success or kill criteria, and recommend whether to proceed, pause, or stop before defining a first product version.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/forjd/startup-ideation-skills/startup-interview-synthesis
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.

Any agent
npx skills add forjd/startup-ideation-skills --skill startup-interview-synthesis
Clone the repo
git clone --depth 1 https://github.com/forjd/startup-ideation-skills

Made for: Claude Code.

Or install startup-ideation-skills, the plugin that ships this one along with the rest of its 6 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for startup-interview-synthesis

README.md
[![agentmods](https://agentmods.dev/badge/skills/forjd/startup-ideation-skills/startup-interview-synthesis/github.svg)](https://agentmods.dev/skills/forjd/startup-ideation-skills/startup-interview-synthesis)
Your own site
<a href="https://agentmods.dev/skills/forjd/startup-ideation-skills/startup-interview-synthesis"><img src="https://agentmods.dev/badge/skills/forjd/startup-ideation-skills/startup-interview-synthesis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for startup-interview-synthesis

Your own site · 80×15
<a href="https://agentmods.dev/skills/forjd/startup-ideation-skills/startup-interview-synthesis"><img src="https://agentmods.dev/badge/skills/forjd/startup-ideation-skills/startup-interview-synthesis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,434 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00053 $0.01434
Opus 5 $0.00026 $0.00717
Sonnet 5 $0.00011 $0.00287
Haiku 4.5 $0.00005 $0.00143

Measured 12d ago against content hash 3ab9b72ebe82, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

startup-interview-synthesis 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 12d 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/startup-interview-synthesis/SKILL.md · 180 lines

How it starts

The opening of the file, as written. The whole thing — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Startup Interview Synthesis

When to use

Use after interviews, outreach replies, paid-audit conversations, smoke-test responses, or validation-test notes have been collected, and before deciding whether to scope a v1.

This skill turns messy qualitative evidence into a decision. It should not convert polite interest into validation.

Core rule

Separate observed behaviour from opinion, compliments, guesses, and founder interpretation. Treat contradictions as useful evidence, not noise to smooth away.

Inputs to request if missing

Ask only for the missing inputs needed to make the synthesis credible:

Problem statement:
Target user:
Validation goal:
Interview notes or outreach replies:
Test setup:
Success / kill criteria:
Evidence packet so far:

If the user has raw notes, synthesize from them. If they only have a summary, mark confidence lower and ask for exact quotes, commitments, and objections.

Workflow

  1. Normalize the notes by respondent, role, segment, source, and date if available.
  2. Extract evidence as short claims tied to exact quotes or observed behaviour.
  3. Classify each signal as Strong, Mixed, Weak, or Noise.
  4. Separate problem reality, buyer/budget, urgency, workaround, reachability, willingness-to-pay, why-now, and behavioural commitment.
  5. Look for contradictions between respondents, segments, and stated intent versus behaviour.
  6. Identify the strongest evidence for and against the idea.
  7. Decide whether the validation criteria were met, missed, or remain inconclusive.
  8. Update the evidence packet with a proceed, narrow, retest, park, or kill gate.

Evidence quality rubric

Strong signals:

  • A respondent describes a recent real instance with cost, workaround, and consequences.
  • The buyer or budget owner is identified and reachable.
  • Someone agrees to a concrete next step: introduction, paid audit, pilot, LOI, trial, data share, or calendar follow-up.
  • The same pain appears across several similar users without being prompted.
  • A respondent already spends time, money, political capital, or risk budget on the workaround.

Read the full file on GitHub · 180 lines

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. 12d ago First seen · 180 lines · 53 tokens per session scan A 3ab9b72ebe82

Subscribe to this mod's changes

startup-interview-synthesis is a skill published in the GitHub repository forjd/startup-ideation-skills (2 stars, last pushed 2mo ago), licensed MIT. It adds 53 tokens to every session and 1,434 once invoked, about $0.0003 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.