Getting it into your agent
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npx skills add jeffreytse/grimoire-core --skill apply-earnings-myopia-defensegit clone --depth 1 https://github.com/jeffreytse/grimoire-coreWrote 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.
[](https://agentmods.dev/skills/jeffreytse/grimoire-core/apply-earnings-myopia-defense)<a href="https://agentmods.dev/skills/jeffreytse/grimoire-core/apply-earnings-myopia-defense"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/apply-earnings-myopia-defense/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.
<a href="https://agentmods.dev/skills/jeffreytse/grimoire-core/apply-earnings-myopia-defense"><img src="https://agentmods.dev/badge/skills/jeffreytse/grimoire-core/apply-earnings-myopia-defense.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00087 | $0.02252 |
| Opus 5 | $0.00044 | $0.01126 |
| Sonnet 5 | $0.00017 | $0.00450 |
| Haiku 4.5 | $0.00009 | $0.00225 |
Grade A, and why
apply-earnings-myopia-defense 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 9d 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.
How it starts
The opening of the file, as written. The whole thing — 67 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apply Earnings Myopia Defense
Before letting quarterly-earnings pressure cut or delay a genuinely positive-long-term-value investment — R&D, infrastructure, maintenance — recognize this as a specific, well-documented, measurable cause of real value destruction, and build structural protections that keep long-term investment decisions insulated from short-term reporting pressure.
Why This Is Best Practice
Why best: This is not a vague complaint that "companies think too short-term" — Graham, Harvey & Rajgopal's research specifically measured how often financial executives would sacrifice a project with genuinely positive long-term value specifically to hit a quarterly earnings target, and found this trade-off is common, deliberate, and widely acknowledged by the executives making it, not an accidental byproduct of poor planning. Because the mechanism is specific and measurable (earnings-target pressure causing a deliberate cut to positive-NPV long-term investment), the defense is also specific: structurally reduce or eliminate the short-term reporting pressure that creates the incentive to make this trade-off, rather than relying on individual managers to resist it through willpower alone.
Graham, Harvey & Rajgopal (2005): This widely cited survey of over 400 financial executives found a striking, explicit result: a majority of surveyed CFOs stated they would decrease discretionary spending on R&D, advertising, and maintenance — even when they believed such spending had genuine long-term positive value — specifically to meet a quarterly earnings benchmark. The survey also found executives placed a high priority on meeting earnings benchmarks (matching the prior year's earnings, meeting analyst consensus, and reporting smooth, low-volatility earnings) even above maximizing the firm's actual long-term value, and were explicit that this reflected real, deliberate trade-offs rather than an oversight.
Bushee (1998): Provided empirical, firm-level evidence for the same mechanism from the opposite direction — measuring actual R&D spending against a firm's institutional ownership composition, Bushee found that firms with a higher proportion of "transient" institutional investors (those trading on short-term earnings performance rather than holding for long-term value) were significantly more likely to cut R&D spending specifically to avoid missing short-term earnings expectations, compared to otherwise similar firms with more long-term-oriented ownership — directly linking the composition of a company's investor base to the severity of this specific underinvestment pattern.
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.
- 9d ago First seen · 67 lines · 87 tokens per session scan A 2f2a44e3fc22
apply-earnings-myopia-defense is a skill published in the GitHub repository jeffreytse/grimoire-core (4 stars, last pushed 24d ago), licensed MIT. It adds 87 tokens to every session and 2,252 once invoked, about $0.0004 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 2026-09-03.
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