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SKILL verified MIT Self-run

Value Realization

skill-natan-mohart-24-strategy-skills-for-claude-value-realization · by Natan-Mohart

Closes the loop that every other financial-case skill in this pack opens — checks realized results against the original business case, full-potential diagnostic, or synergy case line by line, and attributes the gap to assumption error, execution, or external shock. Use whenever the user wants a post-implementation review, wants to check if an initiative or deal actually delivered its promised val…

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Install

$ agentstack add skill-natan-mohart-24-strategy-skills-for-claude-value-realization

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

Value Realization

When to use

Use 6-18 months after a business case, full-potential diagnostic, or synergy case was approved, to check whether it actually delivered. Every skill in this pack that produces a projection (business-case-builder, full-potential-diagnostic, synergy-case-builder) has no accountability loop without this step — a business case with no eventual value-realization check tends to get more optimistic over time, since no one ever pays for being wrong.

What it does

Compares the original projection's driver-level numbers against actuals at the same granularity, attributes material variances to a specific cause (assumption error, execution gap, or external shock), and states plainly whether the initiative is on track but delayed, or genuinely off track — then feeds the finding back into how future cases in this organization get built.

Method

  1. Pull the original projection at driver level, not just the headline number — the same granularity business-case-builder, full-potential-diagnostic, or synergy-case-builder produced.
  2. Gather actuals at the same driver-level granularity and time periods, so the comparison is apples to apples.
  3. Compute variance per driver, not just the bottom line — offsetting errors can make a headline number look fine while hiding that every underlying driver missed in a different direction.
  4. Attribute each material variance to one cause: assumption error (the input was wrong from the start — check against any assumption-audit that exists), execution gap (the assumption was reasonable, delivery fell short), or external shock (outside anyone's reasonable forecast).
  5. State the verdict plainly: on track but behind schedule (needs a revised timeline, not a new decision), or genuinely off track (needs a real decision about continuing, adjusting, or stopping).
  6. Feed the recurring cause back into practice. If assumption error keeps showing up across past reviews, that's a signal the assumption-audit step is being skipped or done too lightly upstream — name it as a process fix.

Inputs

  • The original projection (business case, full-potential diagnostic, or synergy case) at driver-level detail
  • Actual results at the same granularity and time periods
  • Any assumption-audit findings from the original case, if available

Output format

Driver-by-driver projected-vs-actual comparison with variance; cause attribution per material variance; an explicit on-track-but-delayed vs. off-track verdict; one process-level learning fed back into future case-building.

Example

An initiative projected at $3M NPV within 18 months is reviewed at month 12: revenue tracks 15% below plan (an overly optimistic conversion-rate assumption, an assumption error) while costs run 10% under plan (an execution win). The blended NPV still looks roughly on track, but the review flags the revenue-driver miss as the real signal worth revisiting, rather than declaring the case validated because the bottom line happens to still look fine.

Common pitfalls

  • Checking only the bottom-line number, missing that offsetting driver errors can accidentally produce a healthy-looking total.
  • Treating every miss as an execution failure without checking whether the original assumption was ever realistic.
  • Skipping the review once a case has served its purpose of getting funding approved, breaking the accountability loop for every future case.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.